Lars Magnus Hvattum

• Knudseth, Sunniva Haukvik; Molland, Even; Hoff, Arild; Hvattum, Lars Magnus & Oppen, Johan (2024). Decision support for allocating farmed fish to customer orders using a bi-objective optimization model. Decision Making in Manufacturing and Services. ISSN 1896-8325. 16, p. 67–90. doi: 10.7494/dmms.2022.16.5019. Full text in Research Archive Show summary

  Aquaculture is an important industry in certain coastal areas. Focusing on farming of salmon and trout, an operational planning problem arises with the goal of allocating supply of fish to demand expressed through customer orders. This paper provides a conceptual model of such a planning problem, defines a corresponding bi-objective mathematical programming model. The problem is novel with respect to the structure of the transportation of fish, and the rules for satisfying customer orders with respect to fish size, quality, certification, and health status. Computational experiments are conducted to gain further insights into the use of the provided model to provide support for planners involved in the operational decision making. Results indicate that the bi-objective optimization model can be useful in situations where supply is insufficient to cover all the demand within a given planning horizon.

• Shaabani, Homayoun; Hvattum, Lars Magnus; Laporte, Gilbert & Hoff, Arild (2023). A goal programming model for the stability analysis of a maritime inventory routing replanning problem. Maritime Transport Research. ISSN 2666-822X. 5(December). doi: 10.1016/j.martra.2023.100101.
• Gjøen, Phillip Sa-Ut; Hvattum, Sofus August; Moltubak, Eirik Malme & Hvattum, Lars Magnus (2023). When is 2 better than 3 in basketball? Statistica Applicata. ISSN 1125-1964. 35(1), p. 1–15. doi: 10.26398/IJAS.0035-003. Show summary

  A recent trend in basketball is that teams are taking more shots outside of the three-point line and fewer shots inside. This is an advantage since the expected number of points scored, in general, is slightly higher for three-point shots. Through simulations, this paper shows that there are game situations where a strategy of taking fewer three-point attempts at the expense of more two-point attempts will improve the probability of winning the game. Keywords: simulation, coaching, strategy, sports

• Skålnes, Jørgen; Ben Ahmed, Mohamed ; Hvattum, Lars Magnus & Stålhane, Magnus (2023). New benchmark instances for the inventory routing problem. European Journal of Operational Research. ISSN 0377-2217. 313(3), p. 992–1014. doi: 10.1016/j.ejor.2023.08.010. Full text in Research Archive Show summary

  The existing sets of benchmark instances for the inventory routing problem (IRP) have been beneficial for investigating and illustrating the properties of the problem. However, they possess certain features and design choices that are not necessarily representative of all real-world IRPs. Therefore, we propose a new collection of 270 real-world-like instances ranging from 10 to 200 customers. These instances vary in terms of the number of vehicles and their capacity, the length of the planning horizon, the demand structure, and the geographical distribution of customers. Transportation and inventory holding costs resemble costs found in practice. We present an instance space analysis showing that the new instances nicely complement the original instances. To derive lower and upper bounds for each instance, we present computational experiments with two high-quality solution methods: a matheuristic and an exact branch-and-cut method. The results confirm that the new set of instances is hard to solve with the proposed methods, and they demonstrate the need for developing new solution methods. Keywords: distribution, test instance, branch-and-cut, matheuristic, vendor-managed inventory

• Fagerholt, Kjetil; Hvattum, Lars Magnus; Papageorgiou, Dimitri J. & Urrutia, Sebastián (2023). Maritime inventory routing : recent trends and future directions. International Transactions in Operational Research. ISSN 0969-6016. 30(6), p. 3013–3056. doi: 10.1111/itor.13313. Full text in Research Archive Show summary

  We review recent literature pertaining to the maritime inventory routing problem (MIRP), a stimulating, albeit niche, subclass of vendor-managed inventory problems. MIRPs deal with optimally distributing products with a (typically heterogeneous) vessel fleet between production and consumption ports with inventory tracking and inventory limits. We present two mixed-integer linear programming models for the MIRP—one based on discrete time, the other based on continuous time—and we discuss the advantages and disadvantages of each of the two modeling approaches. In surveying more than 50 papers spanning the decade 2013–2023, we investigate MIRP variants from many different applications and discuss how these have been modeled and solved. Our purpose is to provide a comprehensive overview of state-of-the-art MIRP research published in this period, collated along multiple dimensions. In addition to providing information about available test instances, we highlight recent trends and interesting avenues for future research. As such, we believe this survey will be useful to students, researchers, and practitioners in this domain.

• Ben Ahmed, Mohamed ; Hvattum, Lars Magnus & Agra, Agostinho (2023). The effect of different mathematical formulations on a matheuristic algorithm for the production routing problem. Computers & Operations Research. ISSN 0305-0548. 155(July), p. 1–19. doi: 10.1016/j.cor.2023.106232. Show summary

  We perform an experimental study to evaluate the performance of a matheuristic for the production routing problem (PRP). First, we develop a basic matheuristic that prescribes starting from a partial initial solution, completing it using a sequence of constructive heuristics, and improving it using a general-purpose mixed-integer programming heuristic. Next, we investigate the effect of three state-of-the-art mathematical formulations on the proposed matheuristic convergence. The formulations are implemented and tested with and without the use of valid inequalities. In addition, by suggesting different techniques to generate a feasible starting solution for our matheuristic, we assess the contribution of an initial solution to the matheuristic’s overall performance. We conduct extensive computational experiments on benchmark data instances for the PRP. The results show that a proper choice of an embedded mathematical formulation depends on the data instances’ features, such as the number of customers and the length of the planning horizon. The comparisons undertaken in this study indicate that having a better initial solution does not necessarily lead to finding a better final solution. Keywords: lot sizing, inventory routing, mixed integer formulation, valid inequality, proximity search, experimental analysis

• Shaabani, Homayoun; Hoff, Arild; Hvattum, Lars Magnus & Laporte, Gilbert (2023). A matheuristic for the multi-product maritime inventory routing problem. Computers & Operations Research. ISSN 0305-0548. 154(June), p. 1–19. doi: 10.1016/j.cor.2023.106214. Show summary

  This paper considers a multi-product maritime inventory routing problem in which the routes of the vessels are determined while inventories in the ports must remain within given bounds. Since there is more than one product, each port can be a consumption port for one product and a production port for another product. We propose a matheuristic to deal with large-size instances with a planning horizon of 60 days. The first phase of the heuristic identifies a subset of the arcs in order to use them as input parameters for the second phase. In the second phase, a mathematical model is solved with the selected arcs fixed. These two phases are iterated until a stopping criterion is satisfied. The solutions produced by the matheuristic are compared with those obtained by CPLEX. Comparing the single-product version of the problem with the multi-product version revealed that instances with multiple products require significantly more run time compared with the single-product instances.

• Moazzeni, Sahar; Darmian, Sobhan Mostafayi & Hvattum, Lars Magnus (2023). Multiple criteria decision making and robust optimization to design a development plan for small and medium-sized enterprises in the east of Iran. Operational Research. ISSN 1109-2858. 23. doi: 10.1007/s12351-023-00761-1. Show summary

  This paper is based on a project of developing small and medium-sized enterprises in South Khorasan, Iran. A combination of multiple criteria decision making and robust multi-objective optimization is used for prioritizing industrial clusters and optimally assigning governmental funds. First, criteria for evaluating clusters are weighted using the best-worst method and clusters are prioritized using the VIKOR method. Second, governmental funding is assigned to the highest priority cluster using robust multi-objective mathematical programming. An innovative method is applied to identify the solution of the Pareto-front with the highest efficiency. In a case study from South Khorasan, computational results show that international market share attraction is the most important criterion and the age of the cluster is the least important criterion in the development of the industrial clusters. The cluster defined for barberry and jujube fruits is determined to be the first-ranked cluster. Most of the total available budget for the development of this cluster is assigned to action plans for marketing and trade development and for investment and financial planning. The proposed methodology thus successfully aided the decision makers to plan their work regarding funding of industrial clusters. We believe that the methodology can be applied as a general tool to help managers of industrial development to better assign governmental funding to develop industrial clusters.

• Abraham, Gyula; Dósa, György; Hvattum, Lars Magnus; Olaj, Tomas Attila Paulsen & Tuza, Zsolt (2023). The board packing problem. European Journal of Operational Research. ISSN 0377-2217. 308(3), p. 1056–1073. doi: 10.1016/j.ejor.2023.01.030. Show summary

  We introduce the board packing problem (BoPP). In this problem we are given a rectangular board with a given number of rows and columns. Each position of the board has an integer value representing a gain, or revenue, that is obtained if the position is covered. A set of rectangles is also given, each with a given size and cost. The objective is to purchase some rectangles to place on the board so as to maximize the profit, which is the sum of the gain values of the covered cells minus the total cost of purchased rectangles. This problem subsumes several natural optimization problems that arise in practice. A mixed-integer programming model for the BoPP problem is provided, along with a proof that BoPP is NP-hard by reduction from the satisfiability problem. An evolutionary algorithm is also developed that can solve large instances of BoPP. We introduce benchmark instances and make extensive computer examinations. Keywords: combinatorial optimization, genetic algorithm, binary integer programming, covering, location problems

• Hvattum, Lars Magnus; Kriegl, Marc-André & Čulík, Miroslav (2023). Identifying talent in association football through plus-minus ratings. In Dominicy, Yves & Ley, Christophe (Ed.), Statistics meets sports : what we can learn from sports data. Cambridge Scholars Publishing. ISSN 978-1-5275-9273-5. p. 175–200. Show summary

  This book inscribes itself in the growing context of sports analytics and the combination of data science with sports medicine, which deeply impact the world of sports. Today, ever-more data are being collected and lead to ground-breaking and game-changing new insights. This book provides a solid understanding of these new trends in sports and offers the interested reader with a starting point from which to dive into this blossoming field.

• Bentsen, Håkon & Hvattum, Lars Magnus (2022). Variable neighborhood search for binary integer programming problems. International Journal of Metaheuristics (IJMHeur). ISSN 1755-2176. 8, p. 1–26. doi: 10.1504/IJMHEUR.2022.10052729. Full text in Research Archive Show summary

  General solvers exist for several types of optimisation problems, with the commercially available solvers for mixed integer programming (MIP) being a prime example. Although binary integer programming (BIP) can be used to model a wide variety of important combinatorial optimisation problems, relatively few contributions have been made to develop heuristic algorithms for BIP. This paper examines whether variable neighbourhood search can be successfully used to tackle BIP instances, when avoiding very large neighbourhoods explored by the means of external MIP solvers. The results indicate that methods based on variable neighbourhood search are more successful than exact and heuristic commercial solvers on certain types of instances, while the opposite holds true on others. A general variable neighbourhood search proves very effective on instances with up to 200 variables, in particular some instances that are tightly constrained. Keywords: black-box solver, 0-1 integer programming, variable neighbourhood descent, VND, mathematical programming

• Zojaji, Amir; Soltaniani, Kiarash; Hvattum, Lars Magnus & Urrutia, Sebastián (2022). Cyclic solutions to a maritime inventory routing problem. Maritime Transport Research. ISSN 2666-822X. 3, p. 1–13. doi: 10.1016/j.martra.2022.100074. Show summary

  An inventory routing problem occurs when a company manages inventories both at production sites and consumption sites while also being in charge of the transportation of goods. We consider a maritime inventory routing problem where inventories are located at ports and a single product is transported between these ports using a heterogeneous fleet of vessels. As opposed to standard research on such maritime inventory routing problems, a model is developed that produces cyclic plans that are repeatable. Such plans are more costly than plans found using standard non-cyclic models, but the latter suffer from end-of-horizon effects due to being over-optimistic and making myopic decisions in accordance with an objective of minimizing costs.

• Pluskal, Jaroslav; Šomplák, Radovan; Hrabec, Dušan; Nevrlý, Vlastimír & Hvattum, Lars Magnus (2022). Optimal location and operation of waste-to-energy plants when future waste composition is uncertain. Operational Research. ISSN 1109-2858. 22, p. 5765–5790. doi: 10.1007/s12351-022-00718-w. Show summary

  In many countries, waste management is increasingly geared towards a circular economy, aiming for a sustainable society with less waste generation, fewer landfills, and a higher rate of recycling. Waste-to-Energy (WtE) plants, which convert waste into heat and energy, can contribute to the circular economy by utilizing types of waste that cannot be recycled. Due to the varying quality of sorting and socio-economic conditions in individual regions, the waste composition differs between regions and has an uncertain future development. Waste composition significantly affects the operation of WtE plants due to differences in energy potential. This paper supports strategic capacity planning for waste energy recovery by introducing a two-stage stochastic mixed-integer linear programming model that captures waste composition uncertainty through scenarios of possible future development. The results of the model provide insights into the economics of operation and identify important factors in the sustainability of the waste handling system. The model is demonstrated on an instance with six scenarios for waste management in the Czech Republic for the year 2030. The solution of the proposed model is to build 14 new WtE plants with a total capacity of 1970 kt in addition to the four existing plants with a capacity of 831 kt. The annual energy recovery capacity is expected to increase almost four times to satisfy EU directives that restrict waste landfilling.

• Algendi, Abdalrahman; Urrutia, Sebastián & Hvattum, Lars Magnus (2022). Optimizing production levels in maritime inventory routing with load-dependent speed optimization. Flexible Services and Manufacturing Journal. ISSN 1936-6582. 35(1), p. 111–141. doi: 10.1007/s10696-022-09460-z. Show summary

  Maritime inventory routing problems with load-dependent speed optimization involves determining optimal routes, as well as vessel speeds and loads at these routes, so that inventory limits are satisfied at both production and consumption ports. This paper considers a variant where production rates can be selected from several available alternative production levels, as opposed to the normal situation where production rates are chosen a priori. In both cases, production rates remain constant for the duration of the planning horizon. The effect on transportation costs when considering production levels as decision variables is evaluated. The resulting solutions are compared with solutions obtained when production rates are considered as fixed parameters. Computational experiments on a set of benchmark instances from the literature confirm that the process of determining the optimal production levels plays a crucial role in improving the solutions to maritime inventory routing problems with load-dependent speed optimization. Optimizing the production levels can reduce transportation costs by up to 35%.

• Hvattum, Lars Magnus (2022). Adjusting the order crossover operator for capacitated vehicle routing problems. Computers & Operations Research. ISSN 0305-0548. 148(December), p. 1–8. doi: 10.1016/j.cor.2022.105986. Full text in Research Archive Show summary

  The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. Keywords: vehicle routing problem, genetic algorithm, open source, genetic operator

• Bentsen, Håkon; Hoff, Arild & Hvattum, Lars Magnus (2022). Exponential extrapolation memory for tabu search. EURO Journal on Computational Optimization. ISSN 2192-4406. 10. doi: 10.1016/j.ejco.2022.100028. Full text in Research Archive Show summary

  Tabu search is a well-established metaheuristic framework for solving hard combinatorial optimization problems. At its core, the method uses different forms of memory to guide a local search through the solution space so as to identify high-quality local optima while avoiding getting stuck in the vicinity of any particular local optimum. This paper examines characteristics of moves that can be exploited to make good decisions about steps that lead away from recently visited local optima and towards a new local optimum. Our approach uses a new type of adaptive memory based on a construction called exponential extrapolation. The memory operates by means of threshold inequalities that ensure selected moves will not lead to a specified number of most recently encountered local optima. Computational experiments on a set of one hundred different benchmark instances for the binary integer programming problem suggest that exponential extrapolation is a useful type of memory to incorporate into a tabu search. Keywords: 0-1 Integer programming, binary optimization, adaptive memory, tabu search

• Rodrigues, Filipe; Agra, Agostinho; Hvattum, Lars Magnus & Requejo, Cristina (2022). Weighted iterated local branching for mathematical programming problems with binary variables. Journal of Heuristics. ISSN 1381-1231. 28(3), p. 329–350. doi: 10.1007/s10732-022-09496-2. Full text in Research Archive Show summary

  Local search algorithms are frequently used to handle complex optimization problems involving binary decision variables. One way of implementing a local search procedure is by using a mixed-integer programming solver to explore a neighborhood defined through a constraint that limits the number of binary variables whose values are allowed to change in a given iteration. Recognizing that not all variables are equally promising to change when searching for better neighboring solutions, we propose a weighted iterated local branching heuristic. This new procedure differs from similar existing methods since it considers groups of binary variables and associates with each group a limit on the number of variables that can change. The groups of variables are defined using weights that indicate the expected contribution of flipping the variables when trying to identify improving solutions in the current neighborhood. When the mixed-integer programming solver fails to identify an improving solution in a given iteration, the proposed heuristic may force the search into new regions of the search space by utilizing the group of variables that are least promising to flip. The weighted iterated local branching heuristic is tested on benchmark instances of the optimum satisfiability problem, and computational results show that the weighted method is superior to an alternative method without weights.

• Balogh, János; Dósa, György; Hvattum, Lars Magnus; Olaj, Tomas & Tuza, Zsolt (2022). Guillotine cutting is asymptotically optimal for packing consecutive squares. Optimization Letters. ISSN 1862-4472. 16(9), p. 2775–2785. doi: 10.1007/s11590-022-01858-w. Full text in Research Archive Show summary

  More than half a century ago Martin Gardner popularized a question leading to the benchmark problem of determining the minimum side length of a square into which the squares of sizes 1, 2,..., n can be packed without overlap. Constructions are known for a certain range of n, and summing up the areas yields that a packing in a square of size smaller than N :=√n(n + 1)(2n + 1)/6) is not possible. Here we prove that an asymptotically minimal packing exists in a square of size N +cn+O(√n) with c < 1, and such a packing is achievable with guillotine-cuts. An improved construction is also given for the case where the constraint of guillotine cutting is dropped. Keywords: Square packing · Guillotine cut · Asymptotic analysis · Gardner’s problem · Square the square · Recursive algorithm.

• Hrabec, Dušan; Hvattum, Lars Magnus & Hoff, Arild (2022). The value of integrated planning for production, inventory, and routing decisions : a systematic review and meta-analysis. International Journal of Production Economics. ISSN 0925-5273. 248(June), p. 1–13. doi: 10.1016/j.ijpe.2022.108468. Full text in Research Archive Show summary

  This paper presents a comparison of sequential and integrated planning for the production routing problem, in which production, inventory, and routing decisions must be made. The aim is to estimate the expected value of treating the problems as a whole, rather than making decisions sequentially. In particular, the following research questions are posed: What is the expected cost reduction when combining production, inventory, and routing in a single modeling framework, compared to solving the problems individually in a sequence? Under which circumstances is it most beneficial to tackle an integrated problem? In other words, the goal is to establish whether the solutions obtained by the integration are clearly better than approximate solutions obtained by a more simplified process, and if so, under which circumstances this difference is the most pronounced. To answer these research questions, a systematic review was performed, resulting in a set of 20 relevant articles that were analyzed in depth. For the first research question, computational results from 15 articles were obtained and analyzed through a meta-analysis. The analysis estimated an expected cost savings provided by integration of 11.08%, with a 95% confidence interval of [6.58%, 15.58%]. For the second research question, individual results obtained via sensitivity analyses in 20 relevant articles were summarized qualitatively, enabling insights into how the potential savings by integration is influenced by parameters such as the degrees of freedom, the cost, and the capacity. Keywords: sequential planning, value of integration, distribution, production routing problem

• Bolstad, Kamilla Hamre; Joshi, Manu; Hvattum, Lars Magnus & Stålhane, Magnus (2022). Composing vessel fleets for maintenance at offshore wind farms by solving a dual-level stochastic programming problem using GRASP. Logistics. ISSN 2305-6290. 6(1), p. 1–22. doi: 10.3390/logistics6010006. Full text in Research Archive Show summary

  Background: Dual-level stochastic programming is a technique that allows modelling uncertainty at two different levels, even when the time granularity differs vastly between the levels. In this paper we study the problem of determining the optimal fleet size and mix of vessels performing maintenance operations at offshore wind farms. In this problem the strategic planning spans decades, while operational planning is performed on a day-to-day basis. Since the operational planning level must somehow be taken into account when making strategic plans, and since uncertainty is present at both levels, dual-level stochastic programming is suitable. Methods: We present a heuristic solution method for the problem based on the greedy randomized adaptive search procedure (GRASP). To evaluate the operational costs of a given fleet, a novel fleet deployment heuristic (FDH) is embedded into the GRASP. Results: Computational experiments show that the FDH produces near optimal solutions to the operational day-to-day fleet deployment problem. Comparing the GRASP to exact methods, it produces near optimal solutions for small instances, while significantly improving the primal solutions for larger instances, where the exact methods do not converge. Conclusions: The proposed heuristic is suitable for solving realistic instances, and produces near optimal solution in less than 2 h. View Full-Text Keywords: heuristic, fleet size and mix, offshore wind, uncertainty, multi-horizon

• Ben Ahmed, Mohamed ; Hryhoryeva, Maryia; Hvattum, Lars Magnus & Haouari, Mohamed (2021). A matheuristic for the robust integrated airline fleet assignment, aircraft routing, and crew pairing problem. Computers & Operations Research. ISSN 0305-0548. 137(January), p. 1–14. doi: 10.1016/j.cor.2021.105551. Show summary

  We address an integrated airline scheduling problem that combines three airline planning processes: fleet assignment, aircraft routing, and crew pairing. For a given daily flight schedule, the problem requires simultaneously assigning aircraft and crews to each scheduled flight, taking into account aircraft maintenance restrictions and crew work rules. We propose to solve this complex problem of integrated flight planning while taking into account robustness considerations. In this regard, robustness is achieved by restricting tight connections in the schedule and increasing the number of connections where crews follow the aircraft. We formulate the problem using a very large-scale, yet compact, mixed-integer programming model, and we propose a matheuristic consisting of a decomposition approach and a proximity search algorithm. Computational experiments carried out on real instances from a major airline and having up to 14,014 itineraries, 646 flights, and 202 aircraft provide evidence of the proposed approach’s efficacy. In particular, we find that the average deviation from a conservative bound is at most equal to 0.6%. Keywords: mixed-integer programming, compact formulation, robustness, proximity search

• Van Eetvelde, Hans; Hvattum, Lars Magnus & Ley, Christophe (2021). The probabilistic final standing calculator : a fair stochastic tool to handle abruptly stopped football seasons. AStA Advances in Statistical Analysis. ISSN 1863-8171. 107(1-2), p. 251–269. doi: 10.1007/s10182-021-00416-6. Show summary

  The COVID-19 pandemic has left its marks in the sports world, forcing the full stop of all sports-related activities in the first half of 2020. Football leagues were suddenly stopped, and each country was hesitating between a relaunch of the competition and a premature ending. Some opted for the latter option and took as the final standing of the season the ranking from the moment the competition got interrupted. This decision has been perceived as unfair, especially by those teams who had remaining matches against easier opponents. In this paper, we introduce a tool to calculate in a fairer way the final standings of domestic leagues that have to stop prematurely: our Probabilistic Final Standing Calculator (PFSC). It is based on a stochastic model taking into account the results of the matches played and simulating the remaining matches, yielding the probabilities for the various possible final rankings. We have compared our PFSC with state-of-the-art prediction models, using previous seasons which we pretend to stop at different points in time. We illustrate our PFSC by showing how a probabilistic ranking of the French Ligue 1 in the stopped 2019–2020 season could have led to alternative, potentially fairer, decisions on the final standing.

• Amaral, Heber F.; Urrutia, Sebastián & Hvattum, Lars Magnus (2021). Delayed improvement local search. Journal of Heuristics. ISSN 1381-1231. 27(5), p. 923–950. doi: 10.1007/s10732-021-09479-9. Full text in Research Archive Show summary

  Local search is a fundamental tool in the development of heuristic algorithms. A neighborhood operator takes a current solution and returns a set of similar solutions, denoted as neighbors. In best improvement local search, the best of the neighboring solutions replaces the current solution in each iteration. On the other hand, in first improvement local search, the neighborhood is only explored until any improving solution is found, which then replaces the current solution. In this work we propose a new strategy for local search that attempts to avoid low-quality local optima by selecting in each iteration the improving neighbor that has the fewest possible attributes in common with local optima. To this end, it uses inequalities previously used as optimality cuts in the context of integer linear programming. The novel method, referred to as delayed improvement local search, is implemented and evaluated using the travelling salesman problem with the 2-opt neighborhood and the max-cut problem with the 1-flip neighborhood as test cases. Computational results show that the new strategy, while slower, obtains better local optima compared to the traditional local search strategies. The comparison is favourable to the new strategy in experiments with fixed computation time or with a fixed target.

• Hvattum, Lars Magnus & Gelade, Garry A. (2021). Comparing bottom-up and top-down ratings for individual soccer players. International Journal of Computer Science in Sport. ISSN 1684-4769. 20(1), p. 23–42. doi: 10.2478/ijcss-2021-0002. Full text in Research Archive Show summary

  Correctly assessing the contributions of an individual player in a team sport is challenging. However, an ability to better evaluate each player can translate into improved team performance, through better recruitment or team selection decisions. Two main ideas have emerged for using data to evaluate players: Top-down ratings observe the performance of the team as a whole and then distribute credit for this performance onto the players involved. Bottom-up ratings assign a value to each action performed, and then evaluate a player based on the sum of values for actions performed by that player. This paper compares a variant of plus-minus ratings, which is a top-down rating, and a bottom-up rating based on valuing actions by estimating probabilities. The reliability of ratings is measured by whether similar ratings are produced when using different data sets, while the validity of ratings is evaluated through the quality of match outcome forecasts generated when the ratings are used as predictor variables. The results indicate that the plus-minus ratings perform better than the bottom-up ratings with respect to the reliability and validity measures chosen and that plus-minus ratings have certain advantages that may be difficult to replicate in bottom-up ratings. Keywords: association football, ranking, prediction, plus-minus, validity

• Ben Ahmed, Mohamed ; Okoronkwo, Onyemaechi Linda; Okoronkwo, Edwin Chimezie & Hvattum, Lars Magnus (2021). Long‐term effects of short planning horizons for inventory routing problems. International Transactions in Operational Research. ISSN 0969-6016. 29(5), p. 2995–3030. doi: 10.1111/itor.12998. Full text in Research Archive Show summary

  This paper presents a detailed study concerning the importance of the planning horizon when solving inventory routing problems (IRPs). We evaluate the quality of decisions obtained by solving a finite-horizon IRP. We also discuss the relevance of explicitly considering profit maximization models rather than the traditional cost minimization variant. As a means to this end, we describe four classes of the IRP corresponding to different types of markets. Two of them lead to nonlinear models, which are linearized. Furthermore, we provide a deterministic simulator to evaluate the long-term effects arising from using planning horizons of varying lengths when solving the IRP. A computational study is performed on cases generated from benchmark data instances. The results confirm that the long-term performance of the IRP decisions is, in part, contingent on the length of the selected planning horizon. They also show that considering profit maximization instead of cost minimization leads to different decisions, generating considerably more revenue and profits, albeit not nearly as much as suggested by individual solutions to static IRPs with short planning horizons. Keywords: profit maximization, path flow, linearization, end effect, simulation

• da Silva, Rodrigo Ferreira; Urrutia, Sebastián & Hvattum, Lars Magnus (2021). Extended high dimensional indexing approach for reachability queries on very large graphs . Expert Systems With Applications. ISSN 0957-4174. 181(November), p. 1–11. doi: 10.1016/j.eswa.2021.114962. Full text in Research Archive Show summary

  Given a directed acyclic graph G = (V,A) and two vertices u, v ∈ V , the reachability problem is to answer if there is a path from u to v in the graph. In the context of very large graphs, with millions of vertices and a series of queries to be answered, it is not practical to search the graph for each query. On the other hand, the storage of the full transitive closure of the graph is also impractical due to its O(|V |2) size. Scalable approaches aim to create indices used to prune the search during its execution. Negative indices may be able to determine (in constant time) that a query has a negative answer while positive indices may determine (again in constant time) that a query has a positive answer. In this paper we propose novel scalable approach called LYNX that uses a large number of topological sorts of G as a negative cut index without degrading the query time. A similar strategy is applied regarding a positive cut index. In addition, LYNX proposes a user-defined index size that enables the user to control the ratio between negative and positive cuts depending on the expected query pattern. We show by computational experiments that LYNX consistently outperforms the state-of-the-art approach in terms of query-time using the same index-size for graphs with high reachability ratio. In intelligent computer systems that rely on frequent tests of connectivity in graphs, LYNX can reduce the time delay experience by end users through a reduced query time. This comes at the expense of an increased setup time whenever the underlying graph is updated. Keywords: directed acyclic graphs, topological sorts, reachability queries, graph indexing

• Rodrigues, Filipe; Agra, Agostinho; Hvattum, Lars Magnus & Requejo, Cristina (2021). Weighted proximity search. Journal of Heuristics. ISSN 1381-1231. 27(3), p. 459–496. doi: 10.1007/s10732-021-09466-0. Full text in Research Archive Show summary

  Proximity search is an iterative method to solve complex mathematical programming problems. At each iteration, the objective function of the problem at hand is replaced by the Hamming distance function to a given solution, and a cutoff constraint is added to impose that any new obtained solution improves the objective function value. A mixed integer programming solver is used to find a feasible solution to this modified problem, yielding an improved solution to the original problem. This paper introduces the concept of weighted Hamming distance that allows to design a new method called weighted proximity search. In this new distance function, low weights are associated with the variables whose value in the current solution is promising to change in order to find an improved solution, while high weights are assigned to variables that are expected to remain unchanged. The weights help to distinguish between alternative solutions in the neighborhood of the current solution, and provide guidance to the solver when trying to locate an improved solution. Several strategies to determine weights are presented, including both static and dynamic strategies. The proposed weighted proximity search is compared with the classic proximity search on instances from three optimization problems: the p-median problem, the set covering problem, and the stochastic lot-sizing problem. The obtained results show that a suitable choice of weights allows the weighted proximity search to obtain better solutions, for 75% of the cases, than the ones obtained by using proximity search and for 96% of the cases the solutions are better than the ones obtained by running a commercial solver with a time limit.

• Andersen, Robin; Hassel, Vegard; Hvattum, Lars Magnus & Stålhane, Magnus (2020). In-game betting and the Kelly criterion. Mathematics for applications. ISSN 1805-3610. 9(2), p. 67–81. doi: 10.13164/MA.2020.06. Full text in Research Archive Show summary

  When a bet with a positive expected return is available, the Kelly criterion can be used to determine the fraction of wealth to wager so as to maximize the expected logarithmic return on investment. Several variants of the Kelly criterion have been developed and used by investors and bettors to maximize their performance in inefficient markets. This paper addresses a situation that has not, hitherto, been discussed in academic literature: when multiple bets can be placed on the same object and the available odds, true probabilities, or both, vary over time. Such objects are frequently available in sports betting markets, for example, in the case of in-game betting on outcomes of soccer matches. We adapt the Kelly criterion to support decisions in such live betting scenarios, and provide numerical examples of how optimal bet sizes can sometimes be counter-intuitive.

• Stålhane, Magnus; Bolstad, Kamilla Hamre; Joshi, Manu & Hvattum, Lars Magnus (2020). A dual-level stochastic fleet size and mix problem for offshore wind farm maintenance operations. INFOR: Information Systems and Operational Research. ISSN 0315-5986. 59(2), p. 257–289. doi: 10.1080/03155986.2020.1857629. Show summary

  This paper studies the strategic problem of finding a cost optimal fleet of vessels to support maintenance operations at offshore wind farms. A dual-level stochastic model is formulated, taking into account both long-term strategic uncertainty and short-term operational uncertainty in a single optimization model. The model supports wind farm owners in making strategic decisions regarding the number, placement, charter length, and types of vessels to charter, to meet maintenance demands throughout the lifetime of a wind farm. To evaluate the quality of strategic fleet size and mix decisions, the model also considers the operational decisions of how to utilize the fleet to support maintenance operations. The model accounts for strategic uncertainties that have not been considered in previously developed optimization models for offshore wind, such as uncertainty related to long-term trends in electricity prices and subsidy levels, the stepwise development of wind farms, and technology development in the vessel industry. To solve the proposed stochastic programming model we have developed an ad hoc integer L-shaped method, with customized optimality cuts. The computational experiments show that the proposed method outperforms solving the deterministic equivalent using a commercial MIP solver.

• Turkeš, Renata; Sörensen, Kenneth; Hvattum, Lars Magnus; Barrena, Eva; Chentli, Hayet & Coelho, Leandro C [Show all 20 contributors for this article] (2020). Data for a meta-analysis of the adaptive layer in adaptive large neighborhood search. Data in Brief. ISSN 2352-3409. 33(December), p. 1–10. doi: 10.1016/j.dib.2020.106568. Full text in Research Archive Show summary

  Meta-analysis, a systematic statistical examination that combines the results of several independent studies, has the potential of obtaining problem- and implementation-independent knowledge and understanding of metaheuristic algorithms, but has not yet been applied in the domain of operations research. To illustrate the procedure, we carried out a meta-analysis of the adaptive layer in adaptive large neighborhood search (ALNS). Although ALNS has been widely used to solve a broad range of problems, it has not yet been established whether or not adaptiveness actually contributes to the performance of an ALNS algorithm. A total of 134 studies were identified through Google Scholar or personal e-mail correspondence with researchers in the domain, 63 of which fit a set of predefined eligibility criteria. The results for 25 different implementations of ALNS solving a variety of problems were collected and analyzed using a random effects model. This dataset contains a detailed comparison of ALNS with the non-adaptive variant per study and per instance, together with the meta-analysis summary results. The data enable to replicate the analysis, to evaluate the algorithms using other metrics, to revisit the importance of ALNS adaptive layer if results from more studies become available, or to simply consult the ready-to-use formulas in the summary file to carry out a meta-analysis of any research question. The individual studies, the meta-analysis and its results are described and interpreted in detail in Renata Turkeš, Kenneth Sörensen, Lars Magnus Hvattum, Meta-analysis of Metaheuristics: Quantifying the Effect of Adaptiveness in Adaptive Large Neighborhood Search, in the European Journal of Operational Research. Keywords: meta-analysis, metaheuristics, adaptive large neighborhood search

• Skålnes, Jørgen; Dahle, Lars; Andersson, Henrik; Christiansen, Marielle & Hvattum, Lars Magnus (2020). The Multistage Stochastic Vehicle Routing Problem with Dynamic Occasional Drivers. In Lalla-Ruiz, Eduardo; Mes, Martijn & Voß, Stefan (Ed.), Computational logistics : 11th international conference, ICCL 2020, Enschede, The Netherlands, September 28–30, 2020, Proceedings. Springer. ISSN 978-3-030-59746-7. p. 261–276. doi: https:/doi.org/10.1007/978-3-030-59747-4_17. Show summary

  Widespread use of smart phones and cellular networks allow for new solutions to lower the costs of last mile delivery to customers. We consider a setting where a company not only uses its own fleet of vehicles to deliver products from their store, but can also make use of ordinary people who are already on the road. This may include people who visit the store and are willing to take a detour on their way home for a small compensation. The availability of these occasional drivers is naturally highly uncertain, and we assume that some stochastic information is known about them. This leads to a multistage stochastic vehicle routing problem, with dynamic appearance of vehicles. The contributions of this work is to present a formulation of the multistage stochastic programming problem, identifying what type of problem structures that makes this model superior to that of a two-stage formulation, and when a two-stage formulation can be an adequate simplification. Keywords: stochastic programming, uncertainty, crowdshipping, mixed-integer programming

• Turkeš, Renata; Sörensen, Kenneth & Hvattum, Lars Magnus (2020). Meta-analysis of metaheuristics : quantifying the effect of adaptiveness in adaptive large neighborhood search. European Journal of Operational Research. ISSN 0377-2217. 292(2), p. 423–442. doi: 10.1016/j.ejor.2020.10.045. Show summary

  Research on metaheuristics has focused on (novel) algorithmic development and on competitive testing, both of which have been frequently argued to yield little generalizable knowledge. The main goal of this paper is to promote meta-analysis — a systematic statistical examination that combines the results of several independent studies — as a more suitable way to obtain problem- and implementation-independent insights on metaheuristics. Meta-analysis is widely used in several scientific domains, most notably the medical sciences (e.g., to establish the efficacy of a certain treatment). To the best of our knowledge, this is the first meta-analysis in the field of metaheuristics. To illustrate the approach, we carry out a meta-analysis to gain insights into the importance of the adaptive layer in adaptive large neighborhood search (ALNS). Although ALNS has been widely used to solve a broad range of problems, it has not yet been established whether or not adaptiveness actually contributes to the performance of an ALNS algorithm. A total of 134 studies were identified through Google Scholar or personal e-mail correspondence with researchers in the domain, 63 of which fit our eligibility criteria. After sending requests for data to the authors of the eligible studies, we obtained results for 25 different implementations of ALNS, which were analysed using a random effects model. On average, the addition of an adaptive layer in an ALNS algorithm improves the objective function value by 0.14% (95% confidence interval 0.06% to 0.21%). Although the adaptive layer can (and in a limited number of studies does) have an added value, it also adds complexity and can therefore only be recommended in some specific situations. These findings underline the importance of evaluating the contribution of metaheuristic components. Keywords: metaheuristics, meta-analysis, adaptive large neighborhood search

• Darmian, Sobhan Mostafayi; Moazzeni, Sahar & Hvattum, Lars Magnus (2020). Multi-objective sustainable location-districting for the collection of municipal solid waste : two case studies. Computers & industrial engineering. ISSN 0360-8352. 150(December), p. 1–17. doi: 10.1016/j.cie.2020.106965. Full text in Research Archive Show summary

  This paper presents a multi-objective location-districting optimization model for sustainable collection of municipal solid waste, motivated by strategic waste management decisions in Iran. The model aims to design an efficient system for providing municipal services by integrating the decisions regarding urban area districting and the location of waste collection centers. Three objectives are minimized, given as 1) the cost of establishing collection centers and collecting waste, 2) a measure of destructive environmental consequences, and 3) a measure of social dissatisfaction. Constraints are formulated to enforce an exclusive assignment of urban areas to districts and that the created districts are contiguous. In addition, constraints make sure that districts are compact and that they are balanced in terms of the amount of waste collected. A multi-objective local search heuristic using the farthest-candidate method is implemented to solve medium and large-scale numerical instances, while small instances can be solved directly by commercial software. A set of randomly generated test instances is used to test the effectiveness of the heuristic. The model and the heuristic are then applied to two case studies from Iran. The obtained results indicate that waste collection costs can be reduced by an estimated 20-30 %, while significantly improving the performance with respect to environmental and social criteria. Thus, the provided approach can provide important decision support for making strategic choices in municipal solid waste management. Keywords: multi-objective optimization, local search, best-worst method

• Pantuso, G. & Hvattum, Lars Magnus (2020). Maximizing performance with an eye on the finances: a chance-constrained model for football transfer market decisions. TOP - An Official Journal of the Spanish Society of Statistics and Operations Research. ISSN 1134-5764. 29, p. 583–611. doi: 10.1007/s11750-020-00584-9. Show summary

  Composing a team of professional players is among the most crucial decisions in association football. Nevertheless, transfer market decisions are often based on myopic objectives and are questionable from a financial point of view. This paper introduces a chance-constrained model to provide analytic support to club managers during transfer windows. The model seeks a top-performing team while adapting to different budgets and financial-risk profiles. In addition, it provides a new rating system that is able to numerically reflect the on-field performance of football players and thus contribute to an objective assessment of football players. The model and rating system are tested on a case study based on real market data. The data from the case study are available online for the benefit of future research.

• Hvattum, Lars Magnus (2020). Offensive and defensive plus-minus player ratings for soccer. Applied Sciences. ISSN 2076-3417. 10(20), p. 1–22. doi: 10.3390/app10207345. Full text in Research Archive Show summary

  Rating systems play an important part in professional sports, for example, as a source of entertainment for fans, by influencing decisions regarding tournament seedings, by acting as qualification criteria, or as decision support for bookmakers and gamblers. Creating good ratings at a team level is challenging, but even more so is the task of creating ratings for individual players of a team. This paper considers a plus–minus rating for individual players in soccer, where a mathematical model is used to distribute credit for the performance of a team as a whole onto the individual players appearing for the team. The main aim of the work is to examine whether the individual ratings obtained can be split into offensive and defensive contributions, thereby addressing the lack of defensive metrics for soccer players. As a result, insights are gained into how elements such as the effect of player age, the effect of player dismissals, and the home field advantage can be broken down into offensive and defensive consequences. View Full-Text Keywords: association football; linear regression; regularization; ranking.

• da Silva, Rodrigo Ferreira; Hvattum, Lars Magnus & Glover, Fred (2020). Combining solutions of the optimum satisfiability problem using evolutionary tunneling. The MENDEL Soft Computing journal : International Conference on Soft Computing MENDEL. ISSN 1803-3814. 26(1), p. 23–29. doi: 10.13164/mendel.2020.1.023. Full text in Research Archive Show summary

  The optimum satisfiability problem involves determining values for Boolean vari- ables to satisfy a Boolean expression, while maximizing the sum of coefficients associated with the variables chosen to be true. Existing literature has identified a tabu search heuristic as the best method to deal with hard instances of the prob- lem. This paper combines the tabu search with a simple evolutionary heuristic based on the idea of tunneling between local optima. When combining a set of solutions, variables with common values in all solutions are identified and fixed. The remaining free variables in the problem may be decomposed into several in- dependent subproblems, so that parts of the solutions combined can be extracted and combined in an improved solution. This solution can be further improved by applying the tabu search in an improvement stage. The value of the new heuristic is demonstrated in extensive computational experiments on both existing and new test instances. Keywords: zero-one integer programming, boolean optimization, metaheuristic, tabu search, adaptive memory programming, recombination operator.

• Håland, Else Marie; Wiig, Astrid Salte; Hvattum, Lars Magnus & Stålhane, Magnus (2020). Evaluating the effectiveness of different network flow motifs in association football. Journal of Quantitative Analysis in Sports (JQAS). ISSN 1559-0410. 16(4), p. 311–323. doi: 10.1515/jqas-2019-0097. Full text in Research Archive Show summary

  In association football, a network flow motif describes how distinct players from a team are involved in a passing sequence. The flow motif encodes whether the same players appear several times in a passing sequence, and in which order the players make passes. This information has previously been used to classify the passing style of different teams. In this work, flow motifs are analyzed in terms of their effectiveness in terms of generating shots. Data from four seasons of the Norwegian top division are analyzed, using flow motifs representing subsequences of three passes. The analysis is performed with a generalized additive model (GAM), with a range of explanatory variables included. Findings include that motifs with fewer distinct players are less effective, and that motifs are more likely to lead to shots if the passes in the motif utilize a bigger area of the pitch. Keywords: generalized additive model, passing, regression, soccer

• Eide, Line; Årdal, Gro Cesilie Håhjem; Evsikova, Nataliia; Hvattum, Lars Magnus & Urrutia, Sebastián (2020). Load-dependent speed optimization in maritime inventory routing. Computers & Operations Research. ISSN 0305-0548. 123, p. 1–12. doi: 10.1016/j.cor.2020.105051. Full text in Research Archive Show summary

  Maritime inventory routing problems involve determining optimal routes for seagoing vessels between ports while managing the inventory of each port. Normally, such problems are considered with the vessels operating at fixed sailing speeds. However, the speed of vessels can typically be adjusted within an interval, and the actual fuel consumption depends on both the load and the speed of the vessel. The fuel consumption function combines speed and load in a non-linear manner, but can be approximated through linearization. In this work, to evaluate the importance of taking into account that both speeds and load levels influence the fuel costs, the resulting solutions are contrasted with solutions from the case where speeds and travel costs are taken as constants, as well as the case where speed is a decision, but the cost considered to be independent of the load. For either of these cases, load-dependent speed optimization can be added as a post-processing step. Computational experiments show that combining speed and load do have an impact on the selection of routes in maritime inventory routing problems, and that proper modelling of the fuel consumption can reduce sailing costs significantly. On the test instances considered, taking into account speed while ignoring the load leads to cost savings of around 38%. Considering the fuel consumption as a function of speed and load when planning leads to additional cost savings of 28%.

• Arntzen, Halvard & Hvattum, Lars Magnus (2020). Predicting match outcomes in association football using team ratings and player ratings. Statistical Modelling. ISSN 1471-082X. 21(5), p. 449–470. doi: 10.1177/1471082X20929881. Full text in Research Archive Show summary

  The main goal of this article is to compare the performance of team ratings and individual player ratings when trying to forecast match outcomes in association football. The well-known Elo rating system is used to calculate team ratings, whereas a variant of plus-minus ratings is used to rate individual players. For prediction purposes, two covariates are introduced. The first represents the pre-match difference in Elo ratings of the two teams competing, while the second is the average difference in individual ratings for the players in the starting line-ups of the two teams. Two different statistical models are used to generate forecasts. The first type is an ordered logit regression (OLR) model that directly outputs probabilities for each of the three possible match outcomes, namely home win, draw and away win. The second type is based on competing risk modelling and involves the estimation of scoring rates for the two competing teams. These scoring rates are used to derive match outcome probabilities using discrete event simulation. Both types of models can be used to generate pre-game forecasts, whereas the competing risk models can also be used for in-game predictions. Computational experiments indicate that there is no statistical difference in the prediction quality for pre-game forecasts between the OLR models and the competing risk models. It is also found that team ratings and player ratings perform about equally well when predicting match outcomes. However, forecasts made when using both team ratings and player ratings as covariates are significantly better than those based on only one of the ratings. Key words: Elo rating, competing risk, ordered logit regression, plus-minus rating, survival analysis.

• Husakou, Anatol; Hvattum, Lars Magnus; Danielsen, Ketil & Hoff, Arild (2020). An application of the multi-depot heterogeneous fixed fleet open vehicle routing problem. International Journal of Advanced Operations Management (IJAOM). ISSN 1758-938X. 12(2), p. 142–155. doi: 10.1504/IJAOM.2020.108262. Full text in Research Archive Show summary

  This work describes an application of a multi-depot heterogeneous fixed fleet open vehicle routing problem. A contractor owns a fleet of vehicles with different capacities and running costs. The fleet is used to transport craftsmen from their homes to assigned project sites and back, with some of the craftsmen appointed as drivers while others are passengers. An optimisation model is described that enables the contractor to minimise the transportation costs, and a computational study shows that the model can be solved to optimality for realistically sized instances using a standard mixed-integer programming solver. A variant of the problem is also considered, where the assignment of craftsmen to projects is not fixed a priori. For this variant, several simple heuristic rules are investigated to generate project assignments, and computational results show that they are able to find improved assignments. Keywords: mixed integer programming, assignment, transportation

• Hvattum, Lars Magnus; Tirado, Gregorio & Felipe, Ángel (2020). The double traveling salesman problem with multiple stacks and a choice of container types. Mathematics. ISSN 2227-7390. 8(6), p. 1–11. doi: 10.3390/MATH8060979. Full text in Research Archive Show summary

  The double traveling salesman problem with multiple stacks involves the transportation of goods between two regions. In one region, a vehicle carrying a container visits customers, where pallets of goods are loaded into the container. The container is then shipped to a different region, where another vehicle visits another set of customers where the pallets are unloaded. Pallets are loaded in several rows inside the container, where each row follows the last-in-first-out principle. The standard test instances for the double traveling salesman problem with multiple stacks implies the use of a 45-foot pallet wide container to carry EUR-1 pallets. This paper investigates the effect on transportation costs if an open side container could be used when transporting the pallets. Computational experiments show savings in transportation costs of up to 20%. Moreover, by using a container loaded from the side, rather than from the rear, the defining attributes of the double traveling salesman problem seem to be lost. Keywords: intermodal transportation; vehicle routing; loading; variable neighborhood search.

• Gelade, Garry A. & Hvattum, Lars Magnus (2020). On the relationship between +/- ratings and event-level performance statistics. Journal of Sports Analytics. ISSN 2215-020X. 6(2), p. 85–97. doi: 10.3233/JSA-200432. Full text in Research Archive Show summary

  This work considers the challenge of identifying and properly assessing the contribution of a single player towards the performance of a team. In particular, we study the use of advanced plus-minus ratings for individual football players, which involves evaluating a player based on the goals scored and conceded with the player appearing on the pitch, while compensating for the quality of the opponents and the teammates as well as other factors. To increase the understanding of plus-minus ratings, event-based data from matches are first used to explain the observed variance of ratings, and then to improve their ability to predict outcomes of football matches. It is found that event-level performance statistics can explain from 22% to 38% of the variance in plus-minus ratings, depending on player positions, while incorporating the event-level statistics only marginally improves the predictive power of plus-minus ratings. Keywords: Association football, key performance indicator, adjusted plus-minus, ranking.

• Håland, Else Marie; Wiig, Astrid Salte; Stålhane, Magnus & Hvattum, Lars Magnus (2019). Evaluating passing ability in association football. IMA Journal of Management Mathematics. ISSN 1471-678X. 31(1), p. 91–116. doi: 10.1093/Imaman/dpz004.
• Denstad, Are Gederaas; Ulsund, Einar Askevold; Christiansen, Marielle; Hvattum, Lars Magnus & Tirado, Gregorio (2019). Multi-objective optimization for a strategic ATM network redesign problem. Annals of Operations Research. ISSN 0254-5330. 296, p. 7–33. doi: 10.1007/s10479-019-03224-z. Show summary

  During the last decades, the banking industry has been facing multiple challenges, from changes in regulations and legal systems, to the irruption of new technologies. A constant adaptation to the rapidly changing business ecosystem is therefore required. This paper deals with one type of efficiency improvement that is required from traditional banking operations as a result of the current shift in the industry towards more use of technology. That is, we deal with the decision-making process related to the redesign of existing ATM networks, which is currently being considered by many banks worldwide. This redesign is mainly a consequence of an increased use of electronic payment methods and card transactions, which have made the demand for cash decrease significantly. We describe a multi-objective mathematical programming model to be used as a tool when making strategic decisions regarding the bank ATM network redesign. Total costs and the coverage of customers and turnover are considered as conflicting performance attributes and analyzed through several multi-criteria techniques, namely the weighted sum and Tchebycheff methods and Archimedean goal programming. Among other insights, the results on a realistic case study show that the potential for cost reductions is high and that the consideration of both customer coverage and turnover coverage is crucial for the performance of the network. Keywords: Multi-criteria, Banking, Mathematical programming, Strategic planning.

• Wiig, Astrid Salte; Håland, Else Marie; Stålhane, Magnus & Hvattum, Lars Magnus (2019). Analyzing passing networks in association football based on the difficulty, risk, and potential of passes. International Journal of Computer Science in Sport. ISSN 1684-4769. 18(3), p. 44–68. doi: 10.2478/ijcss-2019-0017. Full text in Research Archive Show summary

  This paper investigates the use of network analysis to identify key players on teams, and patterns of passing within teams, in association football. Networks are constructed based on passes made between players, and several centrality measures are investigated in combination with three different methods for evaluating individual passes. Four seasons of data from the Norwegian top division are used to identify key players and analyze matches from a selected team. The networks examined in this work have weights based on three different aspects of the passes made: their probability of being completed, the probability that the team keeps possession after the completed pass, and the probability of the pass being part of a sequence leading to a shot. The results show that using different metrics and network weights leads to the identification of key passers in different phases of play and in different positions on the pitch. Keywords: network analysis, pagerank, centrality, sport.

• Hvattum, Lars Magnus (2019). A comprehensive review of plus-minus ratings for evaluating individual players in team sports. International Journal of Computer Science in Sport. ISSN 1684-4769. 18(1), p. 1–23. doi: 10.2478/ijcss-2019-0001. Full text in Research Archive Show summary

  The increasing availability of data from sports events has led to many new directions of research, and sports analytics can play a role in making better decisions both within a club and at the level of an individual player. The ability to objectively evaluate individual players in team sports is one aspect that may enable better decision making, but such evaluations are not straightforward to obtain. One class of ratings for individual players in team sports, known as plus-minus ratings, attempt to distribute credit for the performance of a team onto the players of that team. Such ratings have a long history, going back at least to the 1950s, but in recent years research on advanced versions of plus-minus ratings has increased noticeably. This paper presents a comprehensive review of contributions to plusminus ratings in later years, pointing out some key developments and showing the richness of the mathematical models developed. One conclusion is that the literature on plus-minus ratings is quite fragmented, but that awareness of past contributions to the field should allow researchers to focus on some of the many open research questions related to the evaluation of individual players in team sports. Keywords: rating system, ranking, regression, regularization

• Rodrigues, Filipe; Agra, Agostinho; Christiansen, Marielle; Hvattum, Lars Magnus & Requejo, Cristina (2019). Comparing techniques for modelling uncertainty in a maritime inventory routing problem. European Journal of Operational Research. ISSN 0377-2217. 277(3), p. 831–845. doi: 10.1016/j.ejor.2019.03.015. Show summary

  Uncertainty is inherent in many planning situations. One example is in maritime transportation, where weather conditions and port occupancy are typically characterized by high levels of uncertainty. This paper considers a maritime inventory routing problem where travel times are uncertain. Taking into account possible delays in the travel times is of main importance to avoid inventory surplus or shortages at the storages located at ports. Several techniques to deal with uncertainty, namely deterministic models with inventory buffers; robust optimization; stochastic programming and models incorporating conditional value-at-risk measures, are considered. The different techniques are tested for their ability to deal with uncertain travel times for a single product maritime inventory routing problem with constant production and consumption rates, a fleet of heterogeneous vessels and multiple ports. At the ports, the product is either produced or consumed and stored in storages with limited capacity. We assume two stages of decisions, where the routing, the visit order of the ports and the quantities to load/unload are first-stage decisions (fixed before the uncertainty is revealed), while the visit time and the inventory levels at ports are second-stage decisions (adjusted to the observed travel times). Several solution approaches resulting from the proposed techniques are considered. A computational comparison of the resulting solution approaches is performed to compare the routing costs, the amount of inventory bounds deviation, the total quantities loaded and unloaded, and the running times. This computational experiment is reported for a set of maritime instances having up to six ports and five ships. Keywords: transportation, maritime inventory routing, travel times uncertainty, stochastic programming

• Brachner, Markus; Stien, Fredrik Berg & Hvattum, Lars Magnus (2019). A mathematical programming framework for planning an emergency response system in the offshore oil and gas industry. Safety Science. ISSN 0925-7535. 113, p. 328–335. doi: 10.1016/j.ssci.2018.11.031. Show summary

  While accidents in the petroleum industry are commonly connected to oil spill disasters, helicopter accidents are, in terms of incidence rates, a more grave concern in Norway. In this paper we present a range of mathematical programming models and a workflow that support decision makers in planning an emergency response system. For the models that are difficult to solve directly, we introduce a tailor-made solution method. With respect to the optimization objectives and constraints, we particularly focus on the performance metrics of response capacity and response time and show that the optimal solutions can differ remarkably, depending on which metric is in the optimization objective. Moreover, we present a multi-objective model that combines the optimization goals to achieve a balanced solution. A case study shows the concrete application of our framework. Keywords: Emergency preparedness, sea rescue, location models, mathematical programming

• Zaitseva, Anna; Hvattum, Lars Magnus & Urrutia, Sebastián (2018). Profit maximization in inventory routing problems. In ., . (Eds.), 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) . IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5386-6786-6. p. 1230–1234. doi: 10.1109/IEEM.2018.8607713. Show summary

  The inventory routing problem (IRP) deals with the transportation of one product from a producer to multiple consumers, which have given demands and inventory capacities, over a discrete time horizon. The traditional goal of the IRP is to minimize the combination of inventory and transportation costs, while avoiding stock outs at customers. This paper proposes two variations of the IRP with profit maximization. First, when the market situation allows prices to be adjusted, the problem involves finding an optimal balance of volume and margin according to a demand function. Second, when prices are fixed, unit production costs depend on the production volume, which can be adjusted to maximize the profit. Both variations lead to non-linear models, which are linearized and then tested on a selection of standard benchmark instances. Computational results show that considering profit maximization instead of cost minimization leads to different decisions, generating a larger revenue and profit.

• Santini, Alberto; Ropke, Stefan & Hvattum, Lars Magnus (2018). A comparison of acceptance criteria for the adaptive large neighbourhood search metaheuristic. Journal of Heuristics. ISSN 1381-1231. 24(5), p. 783–815. doi: 10.1007/s10732-018-9377-x. Show summary

  Adaptive large neighborhood search (ALNS) is a useful framework for solving difficult combinatorial optimisation problems. As a metaheuristic, it consists of some components that must be tailored to the specific optimisation problem that is being solved, while other components are problem independent. The literature is sparse with respect to studies that aim to evaluate the relative merit of different alternatives for specific problem independent components. This paper investigates one such component, the move acceptance criterion in ALNS, and compares a range of alternatives. Through extensive computational testing, the alternative move acceptance criteria are ranked in three groups, depending on the performance of the resulting ALNS implementations. Among the best variants, we find versions of criteria based on simulated annealing, threshold acceptance, and record-to-record travel, with a version of the latter being consistently undominated by the others. Additional analyses focus on the search behavior, and multiple linear regression is used to identify characteristics of search behavior that are associated with good search performance. Keywords: adaptive large neighbourhood search, simulated annealing, threshold acceptance, record-to-record travel, vehicle routing problem, capacitated minimum spanning tree, quadratic assignment problem 

• Agra, Agostinho; Christiansen, Marielle; Hvattum, Lars Magnus & Rodrigues, Filipe (2018). Robust optimization for a maritime inventory routing problem. Transportation Science. ISSN 0041-1655. 52(3), p. 509–525. doi: 10.1287/trsc.2017.0814. Full text in Research Archive Show summary

  We consider a single product maritime inventory routing problem in which the production and consumption rates are constant over the planning horizon. The problem involves a heterogeneous fleet and multiple production and consumption ports with limited storage capacity. Maritime transportation is characterized by high levels of uncertainty, and sailing times can be severely influenced by varying and unpredictable weather conditions. To deal with the uncertainty, this paper investigates the use of adaptable robust optimization where the sailing times are assumed to belong to the well-known budget polytope uncertainty set. In the recourse model, the routing, the order of port visits, and the quantities to load and unload are fixed before the uncertainty is revealed, while the visit time to ports and the stock levels can be adjusted to the scenario. We propose a decomposition algorithm that iterates between a master problem that considers a subset of scenarios and an adversarial separation problem that searches for scenarios that make the solution from the master problem infeasible. Several improvement strategies are proposed aiming at reducing the running time of the master problem and reducing the number of iterations of the decomposition algorithm. An iterated local search heuristic is also introduced to improve the decomposition algorithm. A computational study is reported based on a set of real instances.

• Sæbø, Olav Drivenes & Hvattum, Lars Magnus (2018). Modelling the financial contribution of soccer players to their clubs . Journal of Sports Analytics. ISSN 2215-020X. 5(1), p. 23–34. doi: 10.3233/JSA-170235. Full text in Research Archive Show summary

  This paper presents a framework for evaluating the financial consequences of player transfers as seen from a club’s perspective. To this end, an objective player rating model is designed based on players’ contribution towards creating a positive goals differential for their team. A regression model is then applied to predict match outcomes as a function of the players involved in a match. Finally, Monte Carlo simulation is used to predict the final league standings and the financial gains obtained as a function of sporting success. The framework isillustrated on player transfers from the 2014-2015 English Premier League season. Keywords: association, football, rating, simulation, regression

• Pasha, Urooj; Hoff, Arild & Hvattum, Lars Magnus (2018). The multi-period fleet size and mix vehicle routing problem with stochastic demands. In Diez, Pedro; Neittaanmäki, Pekka; Periaux, Jacques; Tuovinen, Tero & Bräysy, Olli (Ed.), Computational Methods and Models for Transport. Springer. ISSN 978-3-319-54490-8. p. 121–146. doi: 10.1007/978-3-319-54490-8_9. Show summary

  The multi-period fleet size and mix vehicle routing problem with stochastic demands is a new optimization problem that arises from the need to make strategic fleet sizing decisions while taking into consideration tactical planning and operational uncertainty. The setting is a distribution company that delivers goods to a set of customers and where the expected demand for different customers vary from period to period. The actual demand in a given period is stochastic, and is only revealed when visiting the customer. The objective is to minimize total expected costs, consisting of vehicle acquisition costs, routing costs, and the expected cost of route failures. Route failures occur when a vehicle arrives at a customer with an insufficient amount of goods, resulting in the need to refill the vehicle at the depot. The problem is formulated as a mixed integer programming problem. A heuristic for solving the problem is described and implemented, and a computational study is conducted on a set of varied test instances. Keywords: tabu search, heuristic, scenario, stochastic programming, recourse 

• Hvattum, Lars Magnus (2017). Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer. International Journal of Computer Science in Sport. ISSN 1684-4769. 16(1), p. 50–64. doi: 10.1515/ijcss-2017-0004. Full text in Research Archive Show summary

  Ordinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss. However, the often used ordinal models have an assumption of proportional odds: the influence of an independent variable on the log odds is the same for each outcome. This paper illustrates how ordinal regression models therefore fail to fully utilize independent variables that contain information about the likelihood of matches ending in a draw. However, in practice, this flaw does not seem to have a substantial effect on the predictive accuracy of an ordered logit regression model when compared to a multinomial logistic regression model. Keywords: association football, forecasting, ordered regression

• Raknes, Nora Tangen; Ødeskaug, Katrine; Stålhane, Magnus & Hvattum, Lars Magnus (2017). Scheduling of maintenance tasks and routing of a joint vessel fleet for multiple offshore wind farms. Journal of Marine Science and Engineering (JMSE). ISSN 2077-1312. 5(1). doi: 10.3390/jmse5010011. Full text in Research Archive Show summary

  Maintenance costs related to offshore wind farms are severely limiting their potential for being profitable. This paper proposes a new mathematical model that considers how maintenance tasks should be scheduled and performed by technicians transported using a fleet of dedicated vessels. The model is novel in its combination of modelling several work shifts and including vessels that can stay offshore for several shifts, while handling large maintenance tasks and accurate calculation of downtime costs. Simulation is used to evaluate the performance of the model in its pure form, as well as when solved heuristically using a rolling horizon heuristic. The results indicate that the end-of-horizon effects of the mathematical formulation are handled effectively. Computational experiments also illustrate how the mathematical model coupled with simulation can be used to evaluate strategic decisions regarding the composition of a vessel fleet used to execute maintenance tasks.

• Braaten, Simen V.; Gjønnes, Ola; Hvattum, Lars Magnus & Tirado, Gregorio (2017). Heuristics for the robust vehicle routing problem with time windows. Expert Systems With Applications. ISSN 0957-4174. 77, p. 136–147. doi: 10.1016/j.eswa.2017.01.038. Full text in Research Archive Show summary

  Uncertainty is frequently present in logistics and transportation, where vehicle routing problems play a crucial role. However, due to the complexity inherent in dealing with uncertainty, most research has been devoted to deterministic problems. This paper considers a robust version of the vehicle routing problem with hard time windows, in which travel times are uncertain. A budget polytope uncertainty set describes the travel times, to limit the maximum number of sailing legs that can be delayed. This makes sure that improbable scenarios are not considered, while making sure that solutions are immune to delays on a given number of sailing legs. Existing exact methods are only able to solve small instances of the problem and can be computationally demanding. With the aim of solving large instances with reduced running times, this paper proposes an efficient heuristic based on adaptive large neighborhood search. The computational study performed on instances with different uncertainty levels compares and analyzes the performance of four versions of the heuristic and shows how good quality solutions can be obtained within short computational times.

• Hemmati, Ahmad & Hvattum, Lars Magnus (2017). Evaluating the importance of randomization in adaptive large neighborhood search. International Transactions in Operational Research. ISSN 0969-6016. 24(5), p. 929–942. doi: 10.1111/itor.12273. Show summary

  Randomization is common in many implementations of metaheuristics, and is typically a main ingredient while considering adaptive large neighborhood search (ALNS). This paper considers a standard implementation of ALNS for maritime pickup and delivery problems, identifies seven randomized components in that implementation, and proposes and analyzes simple nonrandomized alternatives to those components. The results reveal that the randomized alternatives perform slightly better for one of seven components, the deterministic alternatives perform better for one component, while the randomized and deterministic alternatives have similar performance for the remaining five components. When analyzing runs with different initial solutions, there seems to be a larger variance in the results obtained with only randomized components, compared to the results with only deterministic components, even when the average results are similar.

• Gullhav, Anders Nordby; Cordeau, Jean-Francois; Hvattum, Lars Magnus & Nygreen, Bjørn (2017). Adaptive large neighborhood search heuristics for multi-tier service deployment problems in clouds. European Journal of Operational Research. ISSN 0377-2217. 259(3), p. 829–846. doi: 10.1016/j.ejor.2016.11.003. Full text in Research Archive Show summary

  This paper proposes adaptive large neighborhood search (ALNS) heuristics for two service deployment problems in a cloud computing context. The problems under study consider the deployment problem of a provider of software-as-a-service applications, and include decisions related to the replication and placement of the provided services. A novel feature of the proposed algorithms is a local search layer on top of the destroy and repair operators. In addition, we use a mixed integer programming-based repair operator in conjunction with other faster heuristic operators. Because of the different time consumption of the repair operators, we need to account for the time usage in the scoring mechanism of the adaptive operator selection. The computational study investigates the benefits of implementing a local search operator on top of the standard ALNS framework. Moreover, we also compare the proposed algorithms with a branch and price (B&P) approach previously developed for the same problems. The results of our experiments show that the benefits of the local search operators increase with the problem size. We also observe that the ALNS with the local search operators outperforms the B&P on larger problems, but it is also comparable with the B&P on smaller problems with a short run time.

• Brachner, Markus & Hvattum, Lars Magnus (2017). Combined emergency preparedness and operations for safe personnel transport to offshore locations. Omega. The International Journal of Management Science. ISSN 0305-0483. 67(March), p. 31–41. doi: 10.1016/j.omega.2016.03.006. Full text in Research Archive Show summary

  Long distances, sparse infrastructure, and adverse environmental conditions make the offshore emergency preparedness system in the High North a big and yet unsolved challenge. This applies in particular to the personnel transport between onshore bases and offshore facilities, which is usually conducted by helicopters. One of the issues to be solved is the sufficient coverage with emergency response units (RUs) in this sparse infrastructure environment. This paper proposes an answer to this issue by using sound logistical concepts, which involves connecting operations and preparedness. A mathematical model is introduced that combines a routing and a covering problem. On one hand, the shortest possible helicopter routes to offshore locations are sought, subject to being within the area covered by the deployed RUs. On the other hand, those RUs are placed so that a contingent helicopter ditching at any point on the chosen routes can be handled within given time limits. The combination of routing and covering forms a trade-off, which gives the decision maker the freedom to balance between the minimization of operational costs related to transport route distances and the long-term costs from response capacity requirements. A computational method that reduces the time to find a solution and allows decision makers to solve real life instances is presented. Computational experiments are conducted with the proposed model, based on prospective production sites in the Barents Sea. Keywords: Covering; Routing; Decision support system; Helicopter; Collaboration.

• Brachner, Markus & Hvattum, Lars Magnus (2016). RescUSim and IPython : an environment for offshore emergency preparedness planning. NIKT: Norsk IKT-konferanse for forskning og utdanning. ISSN 1892-0713. Full text in Research Archive
• Stålhane, Magnus; Vefsnmo, Hanne; Halvorsen-Weare, Elin Espeland; Hvattum, Lars Magnus & Nonås, Lars Magne (2016). Vessel Fleet Optimization for Maintenance Operations at Offshore Wind Farms under Uncertainty. Energy Procedia. ISSN 1876-6102. 94, p. 357–366. doi: 10.1016/j.egypro.2016.09.195. Full text in Research Archive Show summary

  In this paper we consider the problem of determining the optimal fleet size and mix of vessels to support maintenance activities at offshore wind farms. A two-stage stochastic programming model is proposed where uncertainty in demand and weather conditions are taken into account. The model aims to consider the whole life span of an offshore wind farm, and should at the same time remain solvable for realistically sized problem instances. The results from a computational study based on realistic data is provided.

• Tirado, Gregorio & Hvattum, Lars Magnus (2016). Determining departure times in dynamic and stochastic maritime routing and scheduling problems. Flexible Services and Manufacturing Journal. ISSN 1936-6582. 29(3/4), p. 553–571. doi: 10.1007/s10696-016-9242-x. Show summary

  In maritime transportation, decisions are made in a dynamic setting where many aspects of the future are uncertain. However, most academic literature on maritime transportation considers static and deterministic routing and scheduling problems. This work addresses a gap in the literature on dynamic and stochastic maritime routing and scheduling problems, by focusing on the scheduling of departure times. Five simple strategies for setting departure times are considered, as well as a more advanced strategy which involves solving a mixed integer mathematical programming problem. The latter strategy is significantly better than the other methods, while adding only a small computational effort. Keywords: tabu search,uncertainty, scenario, maritime transportation

• Hvattum, Lars Magnus (2016). On the value of aspiration criteria in tabu search. International Journal of Applied Metaheuristic Computing. ISSN 1947-8283. 7(4), p. 39–49. doi: 10.4018/IJAMC.2016100103. Show summary

  Tabu search is a greatly successful metaheuristics, as illustrated through numerous publications showing its use for a range of difficult optimization problems. The tabu search literature is to a certain degree characterized by papers introducing new variations of the search, either presenting new components or proposing changes to existing components. Most often, these new variations are shown to perform well on a particular optimization problem, but are rarely thoroughly analyzed in terms of how they change the search characteristics. This work focuses on the aspiration criterion: A large number of possible variations of aspiration criteria exist, many different variations have been used successfully, and almost no results exist that directly compare the different variations in terms of their performance or behavior. Eight different aspiration criteria are considered, and computational experiments are performed to assess their merit within tabu search implementations for two different combinatorial optimization problems.

• Agra, Agostinho; Christiansen, Marielle; Hvattum, Lars Magnus & Rodrigues, Filipe (2016). A MIP based local search heuristic for a stochastic maritime inventory routing problem. In Paias, Ana; Ruthmair, Mario & Voss, Stefan (Ed.), Computational Logistics - 7th International Conference, ICCL 2016, Lisbon, Portugal, September 7-9, 2016, Proceedings. Springer. ISSN 978-3-319-44895-4. p. 18–34. doi: 10.1007/978-3-319-44896-1_2. Full text in Research Archive Show summary

  We consider a single product maritime inventory routing problem in which the production and consumption rates are constant over the planning horizon. The problem involves a heterogeneous fleet of ships and multiple production and consumption ports with limited storage capacity. In spite of being one of the most common ways to transport goods, maritime transportation is characterized by high levels of uncertainty. The principal source of uncertainty is the weather conditions, since they have a great influence on sailing times. The travel time between any pair of ports is assumed to be random and to follow a log-logistic distribution. To deal with random sailing times we propose a two-stage stochastic programming problem with recourse. The routing, the order in which the ports are visited, as well as the quantities to load and unload are fixed before the uncertainty is revealed, while the time of the visit to ports and the inventory levels can be adjusted to the scenario. To solve the problem, a MIP based local search heuristic is developed. This new approach is compared with a decomposition algorithm in a computational study. Keywords: maritime transportation, stochastic programming, uncertainty, matheuristic

• Tirado, Gregorio & Hvattum, Lars Magnus (2016). Improved solutions to dynamic and stochastic maritime pick-up and delivery problems using local search. Annals of Operations Research. ISSN 0254-5330. 253(2), p. 825–843. doi: 10.1007/s10479-016-2177-5. Show summary

  Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. Keywords: tabu search, uncertainty, scenario routing

• Pasha, Urooj; Hoff, Arild & Hvattum, Lars Magnus (2016). Simple heuristics for the multi-period fleet size and mix vehicle routing problem. INFOR: Information Systems and Operational Research. ISSN 0315-5986. 54(2), p. 97–120. doi: 10.1080/03155986.2016.1149314. Show summary

  Most of the research on vehicle routing problems has focused on the operational or the tactical level. However, any decision made on a strategic level will affect the lower level decisions. One type of strategic decision that has been considered in the literature is to compose an appropriate fleet of different vehicles to perform transportation tasks, which yields the fleet size and mix vehicle routing problem (FSMVRP). This work defines a new variant of the FSMVRP where the customer demands may vary over a set of periods, for example by having different demands on each day of the week. The objective is to find the best fleet composition that can be used to repeatedly fulfil the customer demands, as well as the best routing with that fleet for each of the different periods in the planning horizon. Simple heuristics incorporating a tabu search are implemented to find the fleet composition. Computational results are reported on instances created from a set of standard FSMVRP test instances.

• Hemmati, Ahmad; Hvattum, Lars Magnus; Christiansen, Marielle & Laporte, Gilbert (2016). An iterative two-phase hybrid matheuristic for a multi-product short sea inventory-routing problem. European Journal of Operational Research. ISSN 0377-2217. 252(3), p. 775–788. doi: 10.1016/j.ejor.2016.01.060. Show summary

  This paper considers a multi-product short sea inventory-routing problem in which a heterogeneous fleet of ships transports multiple products from production sites to consumption sites in a continuous time framework. A many-to-many distribution structure is taken into account, which makes it extremely hard to even compute feasible solutions. We propose an iterative two-phase hybrid matheuristic called Hybrid Cargo Generating and Routing (HCGR) to solve the problem. In the first phase the inventory-routing problem is converted into a ship routing and scheduling problem by generating cargoes subject to inventory limits through the use of mathematical programming. In the second phase, an adaptive large neighborhood search solves the resulting ship routing and scheduling problem. The HCGR heuristic iteratively modifies the generated cargoes based on information obtained during the process. The proposed heuristic is compared with an exact algorithm on small size instances; computational results are also presented on larger and more realistic instances.

• Stålhane, Magnus; Hvattum, Lars Magnus & Skaar, Vidar (2015). Optimization of routing and scheduling of vessels to perform maintenance at offshore wind farms. Energy Procedia. ISSN 1876-6102. 80, p. 92–99. doi: 10.1016/j.egypro.2015.11.411. Full text in Research Archive Show summary

  This paper studies the problem of finding the optimal routes and schedules for a fleet of vessels that are to perform maintenance tasks at an offshore wind farm. To solve the problem two alternative models are presented: an arc-flow and a path-flow formulation. Both models are tested on instances of varying numbers of vessels and maintenance tasks. The arc-flow model is solved with commercial software using branch-and-bound. The path-flow model is solved heuristically by generating a subset of the possible routes and schedules, but produces close to optimal solutions using a lot less computing time than the exact arc-flow model.

• Sæbø, Olav Drivenes & Hvattum, Lars Magnus (2015). Evaluating the efficiency of the association football transfer market using regression based player ratings. NIKT: Norsk IKT-konferanse for forskning og utdanning. ISSN 1892-0713. Show summary

  In recent times, the use of quantitative methods to improve decisions within sports has increased. In association football, large amounts of match data has become available. This work first shows how simple match data describing the players on pitch and the time for events such as goals and red cards, can be used to derive an objective player rating. The rating is based on solving a large linear regression model. The resulting player ratings are in turn used as input to a regression model for analyzing transfer fees. It is shown that the performance of players, as reflected in the player ratings, is an important predictor of transfer fees. At the same time, several other important factors that determine the size of transfer fees are identified.

• Hemmati, Ahmad; Stålhane, Magnus; Hvattum, Lars Magnus & Andersson, Henrik (2015). An effective heuristic for solving a combined cargo and inventory routing problem in tramp shipping. Computers & Operations Research. ISSN 0305-0548. 64, p. 274–282. doi: 10.1016/j.cor.2015.06.011. Full text in Research Archive
• Hvattum, Lars Magnus (2015). Playing on artificial turf may be an advantage for Norwegian soccer teams. Journal of Quantitative Analysis in Sports (JQAS). ISSN 1559-0410. 11(3), p. 183–192. doi: 10.1515/jqas-2014-0046. Show summary

  Soccer is as popular as ever, and the sport attracts significant attention from spectators, sponsors, media, and academics. One aspect of the sport that has received relatively little attention, is the effect of the playing surface on the sporting performance of a team. In particular, this paper is concerned with measuring the performance of teams that switch from playing their games on natural grass to playing their games on artificial turf. It is shown that teams, on average, achieve improved results after switching, and that this, at least in part, can be explained by an increased home field advantage.

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• Knudseth, Sunniva Haukvik; Hoff, Arild; Oppen, Johan & Hvattum, Lars Magnus (2023). Decision support for allocating farmed fish to customer orders using a bi-objective optimization model .
• Hoff, Arild; Shaabani, Homayoun; Hvattum, Lars Magnus & Laporte, Gilbert (2023). A matheuristic for the multi-product maritime inventory routing problem.
• Knudseth, Sunniva Haukvik; Molland, Even; Hoff, Arild; Hvattum, Lars Magnus & Oppen, Johan (2022). Decision Support for Allocating Farmed Fish to Customer Orders Using a Bi-objective Optimization Model.
• Langelo, Erik & Hvattum, Lars Magnus (2021). Solving profit-maximizing lot size problems with customer stockpiling and discrete prices. Show summary

  https://iwls2021.sciencesconf.org/

• Ben Ahmed, Mohamed ; Hvattum, Lars Magnus & Haouari, Mohamed (2021). A matheuristic for the robust integrated airline scheduling problem.
• Shaabani, Homayoun; Hoff, Arild; Hvattum, Lars Magnus & Laporte, Gilbert (2021). A matheuristic algorithm for maritime inventory routing problem.
• Hoff, Arild; Hvattum, Lars Magnus & Danielsen, Ketil (2021). An application of the multi-depot heterogeneous fixed fleet open vehicle routing problem.
• Haugen, Kjetil K.; Strandhagen, Jan Ola; Solberg, Harry Arne; Kringstad, Morten; Owren, Brynjulf & Hansson, Lisa [Show all 15 contributors for this article] (2020). Fra toppen av Haugen : svensk norgesmester i verdensklasse. Panorama : nettavis for Høgskolen i Molde.
• Dósa, György; Hvattum, Lars Magnus; Olaj, Tomas Attila Paulsen & Tuza, Zsolt (2020). The board packing problem : packing rectangles into a board to maximize profit. In Vassanyi, Istvan (Eds.), Proceedings of the Pannonian Conference on Advances in Information Technology (PCIT 2020). University of Pannonia, Faculty of Information Technology. ISSN 978-963-396-144-5. p. 10–16.
• Haugen, Kjetil K.; Owren, Brynjulf; Strandhagen, Jan Ola; Kringstad, Morten; Solberg, Harry Arne & Guvåg, Bjørn [Show all 13 contributors for this article] (2019). Fra toppen av Haugen : tabelltips 2019: stadig norgesmester fra Molde. Panorama : nettavis for Høgskolen i Molde.
• Bentsen, Håkon; Hvattum, Lars Magnus & Urrutia, Sebastián (2019). A review of Binary Integer Programming applications and solution methods. Show summary

  Binary Integer Programming (BIP) covers a large variety of different problems, with many real world applications. This work first reviews the scientific literature with the aim of creating an overview of the most important applications of pure BIP models. The literature review is conducted using different search strings in order to find the relevant papers from prominent online databases. The findings are then filtered manually and categorized by application. There are relatively few general purpose solvers for BIP, and computational experiments are conducted to show their performance on benchmark instances from the literature, covering a wide variety of applications. Based on these results, we argue that there is a need for improved general purpose solvers for BIP problems, with a performance level closer to what is found in specialized solvers. Keywords: programming, mixed-integer

• Hvattum, Lars Magnus & Pantuso, Giovanni (2019). Maximizing financial and on-field performances when composing teams in soccer.
• Hvattum, Lars Magnus; da Silva, Rodrigo Ferreira & Glover, Fred (2019). Exploring properties of combining solutions of the Boolean optimization problem.
• Hvattum, Lars Magnus & Hustad, Trond (2019). Moldes viktigste spiller . [Newspaper]. Romsdals Budstikke.
• Hvattum, Lars Magnus (2019). Professor: – Denne spilleren er viktigst for at Molde skal vinne. [Newspaper]. Stavanger Aftenblad.
• Hvattum, Lars Magnus; Zaitseva, Anna & Urrutia, Sebastián (2018). Profit maximization in inventory routing problems.
• Bolstad, Kamilla; Joshi, Manu; Stålhane, Magnus & Hvattum, Lars Magnus (2018). Optimizing the vessel fleet size and mix to perform maintenance at offshore wind farms.
• Dahle, Lars; Andersson, Henrik; Christiansen, Marielle & Hvattum, Lars Magnus (2018). The vehicle routing problem with dynamic occasional drivers - a multistage formulation.
• Hvattum, Lars Magnus & Sæbø, Olav Drivenes (2017). Modelling clubs' financial investment in association football players.
• Hvattum, Lars Magnus (2017). Solving complex optimization problems in practical settings based on findings in the research literature.
• Hasle, Geir; Hvattum, Lars Magnus & Woodruff, David L. (2017). Preface: logistics, optimization and transportation — in memory of the late Arne Løkketangen. Annals of Operations Research. ISSN 0254-5330. 253(2), p. 709–711. doi: 10.1007/s10479-017-2504-5.
• Stålhane, Magnus; Vefsnmo, Hanne; Halvorsen-Weare, Elin Espeland; Hvattum, Lars Magnus & Nonås, Lars Magne (2016). Vessel fleet optimization for maintenance operations at offshore wind farms under uncertainty.
• Stien, Fredrik Berg; Brachner, Markus & Hvattum, Lars Magnus (2016). Distance versus capacity objectives for emergency response systems.
• Hvattum, Lars Magnus & Hemmati, Ahmad (2016). Statistical analysis of randomization in adaptive large neighborhood search.
• Rodrigues, Filipe; Agra, Agostinho; Christiansen, Marielle & Hvattum, Lars Magnus (2016). Dealing with uncertainty in a maritime inventory routing problem.
• Santini, Alberto; Røpke, Stefan & Hvattum, Lars Magnus (2016). A Comparison of Acceptance Criteria for the Adaptive Large Neighbourhood Search Metaheuristic.
• Stålhane, Magnus; Hvattum, Lars Magnus & Skaar, Vidar (2015). Optimization of routing and scheduling of vessels to perform maintenance operations at offshore wind farms.
• Waagbø, Arild Johan & Hvattum, Lars Magnus (2015). Kunstgressfordel på 2,5 poeng per sesong. [Newspaper]. www.panorama.himolde.no.
• Shaabani, Homayoun; Hvattum, Lars Magnus; Laporte, Gilbert & Hoff, Arild (2023). Stability metrics for a maritime inventory routing problem under sailing time uncertainty . Høgskolen i Molde - Vitenskapelig høgskole i logistikk. ISSN 978-82-7962-342-7.

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