Arbeidsområder
- Matematisk modellering og optimeringsmetoder for logistiske planleggingsproblemer
- Planlegging under usikkerhet
- Utvikling av beslutningsstøtte
- Ruteplanlegging
- Offshore energi logistikk
Curriculum vitae
Den nyeste CV er tilgjengelig her (engelsk).
Publikasjoner
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Gribkovskaia, Irina & Slettemark, Gaute Øiestad
(2025).
Tactical helicopter transportation planning for offshore personnel on the Norwegian continental shelf.
Logistics.
9(2).
doi:
10.3390/logistics9020073.
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Background: In offshore energy logistics, contracted helicopters frequently transport personnel to and from offshore installations. Regular and efficient transportation is vital to maintain planned activities at the installations. We focus on tactical helicopter planning from a single heliport for a period of stable weekly transport demands in a heliport operating area on the Norwegian Continental Shelf (NCS). This results in the construction of a repetitive weekly flight program, integrating the selection of helicopter resources optimally matching demand with the generation of a weekly timetable of flights assigning them to start times. The purpose of our research is to develop optimisation-based weekly flight program planning algorithms for energy companies operating on the NCS. Methods: We present a developed two-step solution method sequentially generating possible flights and solving a flight-based integer programming model, and an iterative algorithm based on the decomposition of the flight-based model for the construction of cost-optimal weekly flight programs. Results: The developed algorithms were validated on the real instances from Equinor, the largest NCS energy operator. The decomposition-based algorithm was able to solve to optimality all tested instances, with up to 20 installations served from the heliport within less than 9 min. Conclusions: Equinor logistics planners have tested and verified that the developed flight-based model satisfies the goals and planning policies imposed on the NCS for integrated tactical helicopter planning. Considering the advantages of the decomposition-based algorithm performance in solution quality and speed, energy companies on the NCS find it well-suited as a solution engine in the highly demanded automated decision support tools for tactical helicopter transportation planning.
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Vianna, Igor Girão Peres; Ribas, Paulo Cesar; Ferreira, Virgílio José Martins & Gribkovskaia, Irina
(2025).
Analysis of Fleet Management Policies for Offshore Platform Supply Vessels: The Brazilian Case.
Journal of Marine Science and Engineering (JMSE).
13(4).
doi:
10.3390/jmse13040686.
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Offshore oil and gas activities are crucial in the petroleum industry. Offshore oil and gas installations require different cargo to operate. A heterogeneous fleet of platform supply vessels (PSVs) transports cargo supply to installations. The PSV fleet management in Brazil faces challenges such as the non-availability of the spot market, variations and uncertainties in delivery order demands and due dates, inspection and corrective vessel maintenance, and multiple time windows for service at installations. PSV fleet management aims to satisfy cargo delivery requests in time and quantity, avoid delays, and achieve a balance among delivery service levels, vessel costs, and greenhouse gas emissions. We develop several PSV fleet management policies with delivery service level or fuel consumption goals, composed of new fleet management procedures such as vessel control, vessel assignment to voyages including cargo selection, vessel routing, speed selection, and dynamic re-routing. The results of tests on a real Brazilian case demonstrate that the developed policies with the incorporated fleet management procedures improve fleet performance indicators. The comparative analysis of policies shows their different impacts on indicators, allowing managers to select the best fleet management policy by considering the trade-offs between delivery service level, costs, and emissions, depending on their goals.
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Abu-Marrul, Victor; Martinelli, Rafael; Hamacher, Silvio & Gribkovskaia, Irina
(2022).
Simheuristic algorithm for a stochastic parallel machine scheduling problem with periodic re-planning assessment.
Annals of Operations Research.
ISSN 0254-5330.
320(2),
s. 547–572.
doi:
10.1007/s10479-022-04534-5.
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This paper addresses a parallel machine scheduling problem with non-anticipatory family setup times and batching, considering the task’s stochastic processing times and release dates. The problem arises from a real-life ship scheduling problem in the oil and gas industry. We developed an Iterated Greedy simheuristic with built-in Monte Carlo Simulation to sample the stochastic parameters. We conducted experiments on a set of instances from the literature, considering two simheuristic variants and three uncertainty levels for the stochastic parameters. To highlight the advantages of using simulation to tackle the stochastic problem, the simheuristics are compared against a regular Iterated Greedy metaheuristic, yielding an improvement of up to 16.5% on the objective function’s expected values, with a reduced impact on computational times. During a risk analysis, the Pareto set of solutions is generated to illustrate the trade-off between the expected objective value of the solutions and the conditional value at risk, providing decision-makers with a useful tool to select the schedules that better fit their risk profiles. We use an iterative mechanism to build confidence intervals within a certain confidence level during the method’s simulation step, interrupting the procedure when it reaches the desired error. This strategy’s advantage is highlighted in the computational experiments, which indicates that the number of replications of the simulation is instance and uncertainty level dependent. A periodic re-planning strategy is also used to evaluate the performance of the simheuristic, highlighting the advantages of using the proposed algorithm in a real-life usage situation.
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Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert
(2021).
Periodic supply vessel planning under demand and
weather uncertainty.
INFOR: Information Systems and Operational Research.
ISSN 0315-5986.
59(3),
s. 411–438.
doi:
10.1080/03155986.2021.1907872.
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We solve a periodic supply vessel planning problem under demand
and weather uncertainty, arising in offshore of oil and gas production. Our study is motivated by the case of the Norwegian energy
operator Equinor which supplied us with data. The aim is to determine an optimal fleet composition and a least-cost vessel schedule
under uncertain demand at the installations and uncertain weather
conditions. We present a methodology incorporating a metaheuristic within a discrete-event simulation model which, applied iteratively for the increasing values of reliability level parameters, yields a
vessel schedule of least expected cost.
Keywords: supply vessel planning,
offshore logistics,
uncertainty, reliable vessel
schedules, metaheuristic,
discrete-event simulation, recourse
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Abu-Marrul, Victor; Martinelli, Rafael; Hamacher, Silvio & Gribkovskaia, Irina
(2020).
Matheuristics for a parallel machine scheduling problem with non-anticipatory family setup times : application in the offshore oil and gas industry.
Computers & Operations Research.
ISSN 0305-0548.
128(April),
s. 1–19.
doi:
10.1016/j.cor.2020.105162.
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In this paper, we address a variant of a batch scheduling problem with identical parallel machines and non-anticipatory family setup times to minimize the total weighted completion time. We developed an ILS and a GRASP matheuristics to solve the problem using a constructive heuristic and two MIP-based neighborhood searches, considering two batch scheduling mathematical formulations. The problem derives from a ship scheduling problem related to offshore oil & gas logistics, the Pipe Laying Support Vessel Scheduling Problem (PLSVSP). The developed methods overcome the current solution approaches in the PLSVSP literature, according to experiments carried out on a benchmark of 72 instances, with different sizes and characteristics, in terms of computational time and solution quality. New best solutions are provided for all medium and large-sized instances, achieving a reduction of more than 10% in the objective function of the best case.
Keywords: parallel machine scheduling, family scheduling, batch scheduling, matheuristic, offshore industry logistics, ship scheduling
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Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert
(2019).
Supply vessel routing and scheduling under uncertain demand.
Transportation Research Part C: Emerging Technologies.
ISSN 0968-090X.
104(July),
s. 305–316.
doi:
10.1016/j.trc.2019.04.011.
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We solve a supply vessel planning problem arising in upstream offshore petroleum logistics. A
fleet of supply vessels delivers all the necessary equipment and materials to a set of offshore
installations from an onshore supply base, according to a delivery schedule or sailing plan.
Supply vessels, being the major cost contributor, are chartered on a long-term basis. The planning
of supply vessels implies resolving the trade-off between the cost of the delivery schedule and the
reliability of deliveries on the scheduled voyages, i.e. the service level. The execution of a sailing
plan is affected by stochastic demands at the installations since a high demand fluctuation quite
often leads to insufficient vessel capacity to perform a voyage according to the sailing plan. In
addition, the average demand level at the installations may change over time, while the number
of vessels in the sailing plan remains the same. Maintaining a reliable flow of supplies under
stochastic demand therefore leads to additional costs and reduced service level. We present a
novel methodology for reliable supply vessel planning and scheduling, enabling planners to
construct delivery schedules having a low expected total cost. The methodology involves the
construction of delivery schedules with different reliability levels using an adaptive large
neighborhood search metaheuristic algorithm combined with a discrete event simulation procedure
for the computation of the expected solution cost.
Keywords: maritime logistics, supply vessel planning, recourse, reliable vessel schedules, metaheuristic, simulation
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Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert
(2018).
Robust supply vessel routing and scheduling.
Transportation Research Part C: Emerging Technologies.
ISSN 0968-090X.
90(May),
s. 366–378.
doi:
10.1016/j.trc.2018.03.012.
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We solve the problem of tactical supply vessel planning arising in the upstream offshore petroleum logistics. Supply vessels deliver all the necessary materials and equipment to offshore installations from an onshore supply base according to a delivery schedule. The planning of supply vessels should be done so that their number is minimized and at the same time provide a reliable flow of supplies from the base. The execution of a weekly sailing plan is affected by weather conditions, especially in winter time. Harsh weather conditions increase the number of vessels required to perform the operations as well as the service times at the installations, and thus disrupt the schedule, leading to additional costs and reduced service level. We present a methodology for robust supply vessel planning enabling a trade-off analysis to be made between the schedules’ service level and vessels’ cost. The methodology involves the generation of multiple vessel schedules with different level of robustness using an adaptive large neighbourhood search metaheuristic and a subsequent discrete event simulation procedure for the assessment of the service level. To control the level of robustness we developed a concept of slacks and incorporated it into the metaheuristic algorithm.
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Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert
(2018).
The periodic supply vessel planning problem with flexible departure times and coupled vessels.
Computers & Operations Research.
ISSN 0305-0548.
94(June),
s. 52–64.
doi:
10.1016/j.cor.2018.02.008.
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In upstream offshore petroleum logistics, periodic supply vessel planning plays an important role since it ensures the replenishment of offshore installations on a regular basis with all the necessary equipment and materials from an onshore base. The problem involves the determination of the fleet composition and of the vessel schedules over a given time horizon. We present an extended version of this prob- lem involving flexible departures from the base and the possibility of coupling vessels by swapping their schedules. We propose a voyage-based model that can be solved exactly for small- and medium-size instances. For the solution of larger instances, we have developed an adaptive large neighborhood heuris- tic, which yields optimal or near-optimal solutions relatively fast on small- and medium- size instances. Its performance on larger instances is significantly better than that of alternative algorithms previously developed for the same problem.
Keywords: offshore logistics, vehicle routing, periodic supply vessel planning, adaptive large neighborhood search
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2017).
Environmental performance of speed optimization strategies in offshore supply vessel planning under weather uncertainty.
Transportation Research Part D: Transport and Environment.
ISSN 1361-9209.
57(December),
s. 10–22.
doi:
10.1016/j.trd.2017.08.002.
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Supply vessels serving oil and gas installations at sea are a major emission source of greenhouse gases in offshore logistics. Speed optimization strategies applied in tactical vessel planning significantly reduce fuel consumption and thus emissions. Nevertheless, the environmental performance of these strategies in rough weather conditions is difficult to estimate as the duration of supply vessel operations is weather dependent. In this paper we develop a simulation-optimization tool which estimates the average fuel consumption for weekly vessel schedules. The schedules are constructed by using speed optimized vessel voyages which are simulated under different weather conditions. Results of experiments on real instances show that rough weather conditions increase fuel consumption and costs. The application of speed optimization strategies reduces fuel consumption both in winter and summer, but the reduction may be at the expense of a fixed vessel cost increase in the winter season.
Keywords: green maritime logistics, emissions, speed optimization, supply vessel operations, ship routing and scheduling, weather uncertainty
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Gribkovskaia, Irina; sr, Øyvind Halskau & Kovalyov, Mikhail Y.
(2015).
Minimizing takeoff and landing risk in helicopter pickup and delivery operations.
Omega. The International Journal of Management Science.
ISSN 0305-0483.
55(September),
s. 73–80.
doi:
10.1016/j.omega.2015.02.010.
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The problem of minimizing total helicopter passenger risk caused by takeoffs and landings is studied. There are passenger pickup and delivery demands to be satisfied at given points by flights starting and ending in the same heliport and visiting several points. For each point, the delivery demand is the number of passengers to be transported from the heliport to this point and the pickup demand is the number of different passengers to be transported from this point to the heliport. Each pickup and delivery demand must be satisfied in full by one flight. There are an upper bound on the number of flights and an upper bound on the helicopter passenger capacity. The objective function is a linear combination of the numbers of passengers involved in takeoffs and landings at visited points. A solution is characterized by the number of flights, sets of visited points and their sequences for all flights. Properties of optimal solutions are established. Several cases are proved NP-hard. A quadratic boolean programming formulation and two dynamic programming algorithms are suggested for the general case. Computer experiments demonstrated that they are able to solve real-life instances. Polynomial time algorithms are presented for special cases. Implementation of the suggested solutions into the real helicopter operations should decrease the number of fatalities.
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2015).
Modal split in offshore supply network under the objective of emissions minimization.
Transportation Research Part D: Transport and Environment.
ISSN 1361-9209.
35,
s. 160–174.
doi:
10.1016/j.trd.2014.11.018.
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We study modal split under the objective of emissions minimization in the transportation
of cargo from centralized vendors in the oil and gas industry to decentralized supply bases
on the Norwegian coast. The supply network includes direct road transport and a sea route
along the coast. To gain insight into modal split decisions between road and sea transport
from the shipper’s perspective multi-period mixed integer optimization models are formulated.
Particularly the models give possibilities to examine how weekly demand patterns at
supply bases, cargo commitments to sea transport, storage possibilities at supply bases,
and shipper’s responsibility for a certain share of vessel capacity may effect the emissions
and the modal split. Experiments on real data from an oil and gas company operating offshore
show that the size of the share of vessel capacity and the possibility for storage at
supply bases are the major determinants for a larger shift to environmentally friendly
sea transport. The models can be used as means for making decisions regarding how a shipper
can commit to sea transport to achieve less emissions.
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Norlund, Ellen Karoline; Gribkovskaia, Irina & Laporte, Gilbert
(2015).
Supply vessel planning under cost, environment
and robustness considerations.
Omega. The International Journal of Management Science.
ISSN 0305-0483.
57(B),
s. 271–281.
doi:
10.1016/j.omega.2015.05.006.
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Offshore oil and gas installations need reliable cargo deliveries. The vessels supplying these installations on a periodic basis are expensive and constitute a source of emissions of greenhouse gases. Incorporating vessel speed optimization into the supply vessel planning process may significantly reduce fuel consumption and hence emissions. In addition, speed optimization may yield cost reductions if the number of vessels used does not increase. A main uncertainty factor, especially in the winter season, is the weather conditions which impact sailing and service times. Cost minimization and the application of speed optimization strategies may have implications on the robustness of weekly supply vessel schedules since idle times in the schedules are reduced. We develop a simulation-optimization based methodology that considers costs, emissions and robustness in the generation of weekly supply vessel schedules. Results of analyses conducted on real instances show that robustness requirements may yield both increased emissions and costs in the winter season. However, depending on instance characteristics, different degrees of robustness can be incorporated with both costs and emissions reductions through speed optimization.
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Kisialiou, Yauheni; Gribkovskaia, Irina & Gribkovskaia, Victoria
(2015).
A simulation model for the assessment of the northern sea route troughput.
I Jæger, Bjørn (Red.),
NOFOMA 2015 : Post Conference Proceedings, Molde, 3-5 June 2015, Nordic Logistics Research Network.
Nordic Logistics Research Network.
ISSN 9788279622079.
s. 175–189.
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The purpose of the research is to analyse factors affecting the transit of vessels via the
Northern Sea Route and to develop a simulation tool modelling the transit process
accounting for ice conditions, icebreaker support requirements and convoy formation.
The developed model allows for the assessment of the route throughput measured as the
fraction of transit orders satisfied during the navigation period, and the average order delay
time, affected by the total number of transit orders and the number of available icebreakers.
Keywords: arctic shipping, icebreaker support, sea route throughput, simulation
modelling, transit order Processing.
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Qian, Fubin; Strusevich, Vitaly A.; Gribkovskaia, Irina & sr, Øyvind Halskau
(2015).
Minimization of passenger takeoff and landing risk in offshore helicopter transportation: Models, approaches and analysis.
Omega. The International Journal of Management Science.
ISSN 0305-0483.
51,
s. 93–106.
doi:
10.1016/j.omega.2014.09.002.
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Offshore petroleum industry uses helicopters to transport the employees to and from installations. Takeoff and landing represent a substantial part of the flight risks for passengers. In this paper, we propose and analyze approaches to create a safe flight schedule to perform pickup of employees by several independent flights. Two scenarios are considered. Under the non-split scenario, exactly one visit is allowed to each installation. Under the split scenario, the pickup demand of an installation can be split between several flights. Interesting links between our problem and other problems of combinatorial optimization, e.g., parallel machine scheduling and bin-packing are established. We provide worst-case analysis of the performance of some of our algorithms and report the results of computational experiments conducted on randomly generated instances based on the real sets of installations in the oil fields on the Norwegian continental shelf. This paper is the first attempt to handle takeoff and landing risk in a flight schedule that consists of several flights and lays ground for the study on more advanced and practically relevant models.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2014).
Fleet Sizing for Offshore Supply Vessels with Stochastic Sailing and Service Times.
Procedia Computer Science.
31,
s. 939–948.
doi:
10.1016/j.procs.2014.05.346.
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In this paper we address a supply vessel planning problem arising in servicing oil and gas offshore installations. Supply vessels provide offshore installations with necessary supplies on periodic basis from offshore supply bases according to weekly sailing schedules. The execution of weekly schedules during the year is affected by weather conditions influencing on sailing time and service duration at installations. When the contracted vessel cannot complete a voyage before the start of its next planned voyage, a vessel from the spot market is hired to perform it. Deciding on the number of supply vessels hired to perform operations from a supply base for a year ahead has a strong economic effect on the total annual vessel costs. We present a discrete-event simulation model for evaluation of alternative fleet size configurations taking into consideration uncertainty in weather conditions and future spot vessel rates. The model is validated and tested on real data.
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Sopot, Eugen & Gribkovskaia, Irina
(2014).
Routing of Supply Vessels to with Deliveries and Pickups of Multiple Commodities.
Procedia Computer Science.
31,
s. 910–917.
doi:
10.1016/j.procs.2014.05.343.
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This paper considers a single vehicle routing problem with pickups and deliveries of multiple commodities where each customer requires both pickup and delivery of several types of goods from a single depot. This problem arises in offshore upstream logistics and is relevant for the oil and gas companies operating offshore. Offshore installations need to be supplied with several types of goods from an onshore base, and also some cargo need to be transported from the installations back to the base. Supply operations from and to the base are performed by supply vessels, which have separate compartments for different types of cargo. In this paper we present a mathematical formulation for the problem and describe a metaheuristic algorithm yielding non- Hamiltonian routes where customers may be visited once or twice. Computational tests show that the algorithm outperforms CPLEX optimization solver in speed on instances of medium size and generates high quality solutions for large-size instances compared to the Unified Tabu Search algorithm.
Keywords: vehicle routing; pickup and delivery; multiple commodities; metaheuristics; offshore logistics.
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2013).
Reducing emissions through speed optimization in supply vessel operations.
Transportation Research Part D: Transport and Environment.
ISSN 1361-9209.
23,
s. 105–113.
doi:
10.1016/j.trd.2013.04.007.
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This paper examines how optimizing sailing speeds can reduce supply vessels emissions in the upstream supply chain to offshore installations. We introduce several speed optimization strategies to be used in construction of periodic vessel schedules. The strategies consider vessel waiting times before the start of service at installations and at supply base. Tests carried out on real instances from Statoil’s activities on the Norwegian continental shelf indicate that a 25% emissions and fuel cost reductions can be achieved without fleet size increase.
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Shyshou, Aliaksandr; Gribkovskaia, Irina; Laporte, Gilbert & Fagerholt, Kjetil
(2013).
A Large Neighbourhood Search Heuristic for a Periodic Supply Vessel Planning Problem Arising in Offshore Oil and Gas Operations.
INFOR: Information Systems and Operational Research.
ISSN 0315-5986.
50(4),
s. 195–204.
doi:
10.3138/infor.50.4.195.
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The periodic supply vessel planning problem arises in supply operations performed by a
heterogeneous fleet of vessels operating from an onshore base to offshore installations. These vessels
must supply the installations on a periodic basis. Given a planning horizon, the problem consists of
determining the fleet composition as well as the vessel schedules. This paper proposes a large
neighbourhood search heuristic capable of solving large instances of the problem. On small instances
for which an optimal solution is known, the heuristic consistently finds optimal or near-optimal
solutions. It can also solve larger instances which are intractable by an exact algorithm.
Keywords: Maritime transportation, offshore logistics, routing and scheduling, large neighbourhood
search heuristic.
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Qian, Fubin; Gribkovskaia, Irina; Laporte, Gilbert & sr, Øyvind Halskau
(2012).
Passenger and pilot risk minimization in offshore helicopter transportation.
Omega. The International Journal of Management Science.
ISSN 0305-0483.
40(5),
s. 584–593.
doi:
10.1016/j.omega.2011.11.003.
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In the offshore petroleum industry, employees are transported to and from the offshore installations by
helicopter, which represents a major risk. This paper analyzes how to improve transportation safety by
solving the helicopter routing problem with a risk objective expressed in terms of expected number of
fatalities. A mathematical model is proposed and a tabu search heuristic is applied to this problem.
Three routing policies are considered: a direct routing policy, a Hamiltonian routing policy, and a
general routing policy. Extensive computational experiments are conducted on instances derived from
real data in order to assess and compare these policies under a travel time, a passenger risk and a
combined passenger and pilot risk objective. Several management insights can be derived from this
study. In particular, our results show that passenger transportation risk can be reduced by increasing
travel time at the expense of pilot risk. This can be achieved through a reduction of the average number
of passengers onboard by applying either a Hamiltonian or a general routing policy. Our methodology
can also be used to derive an equitable distribution of risk between passengers and pilots, considering
that pilots fly much more frequently than passengers.
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Qian, Fubin; Gribkovskaia, Irina & sr, Øyvind Halskau
(2011).
Helicopter routing in the Norwegian oil industry : including safety concerns for passenger transport.
International Journal of Physical Distribution & Logistics Management.
ISSN 0960-0035.
41(4),
s. 401–415.
doi:
10.1108/09600031111131959.
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PURPOSE - In the Norwegian offshore oil industry, helicopters have been used as a major mode of transporting personnel to and from offshore installations for decades. Helicopter transportation represents one of the major risks for offshore employees. The purpose of this paper is to study the safety of helicopter transportation in terms of the expected number of fatalities on an operational planning level. DESIGN/METHODOLOGY/APPROACH - Based on an analysis of helicopter accidents, this paper proposes a mathematical model that can aid in the planning of routes for the fleet in order to minimize the expected number of fatalities. FINDINGS - A theorem proven in this paper tells that hub-and-spoke configuration is the best way of routing helicopters in terms of minimizing expected number of fatalities. Computational results indicate that the expected number of fatalities may be reduced at the expense of longer travel time by implementing the proposed method into planning of routes for helicopter fleet. RESEARCH LIMITATIONS/IMPLICATIONS - The main limitation is the present inability to solve large problem instances. PRACTICAL IMPLICATIONS - The suggested tool is able to provide decision makers with a set of solutions from which they can choose the one with the best trade-off between travel time and transportation safety. ORIGINALITY/VALUE - The mathematical model and theoretical results for route planning with a safety-based objective are original.
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Gribkovskaia, Irina; Kurhuzava, Lidziya & Svirydava, Yuliya
(2011).
Development of routing planning tools for a distribution company.
I Hammervoll, Trond (Red.),
The 23rd Annual NOFOMA Conference 9–10 June 2011, Harstad, Norway: Logistics and Supply Chain Management in a High North perspective: Conference proceedings.
Nordic Logistics Research Network.
ISSN 9788245302288.
s. 405–421.
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Purpose of this paper
The purpose of the paper is to describe a new routing planning problem arising in goods
distribution from warehouse to set of customers with requirements on period of service,
and to develop appropriate and efficient solution tools for the problem.
Design/methodology/approach
Objectives were achieved by applying optimization modelling and algorithmic tools such
as mixed-integer linear programming problem formulation, design of route construction
heuristics, and implementation of shortest path algorithm on a road graph.
Findings
Formulation of a vehicle routing problem with new characteristics arising in practical
applications and development of original solution tools for the formulated problem.
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Shyshou, Aliaksandr; Gribkovskaia, Irina & Barceló, Jaume
(2010).
A simulation study of the fleet sizing problem arising in offshore anchor handling operations.
European Journal of Operational Research.
ISSN 0377-2217.
203(1),
s. 230–240.
doi:
10.1016/j.ejor.2009.07.012.
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A fleet sizing problem arising in anchor handling operations related to movement of offshore mobile units is presented in this paper. Typically, the intensity of these operations is unevenly spread throughout the year. The operations are performed by dedicated vessels, which can be hired either on the long-term basis or on the spot market. Spot rates are frequently a magnitude higher than long-term rates, and vessels are hired on the spot market if there is a shortage of long-term vessels to cover the ongoing anchor handling operations. Deciding the cost-optimal fleet of vessels on the long-term hire to cover future operations is a problem facing offshore oil and gas operators. This decision has a heavy economic impact as anchor handling vessels are among the most expensive ones. The problem is highly stochastic because durations of anchor handling operations vary and depend on uncertain weather conditions. Moreover, future spot rates for anchor handling vessels are extremely volatile. The objective of this paper is to describe a simulation model for the fleet sizing problem. The study was initiated by the largest Norwegian offshore oil and gas operator and has received considerable acceptance among the planners.
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Gribkovskaia, Irina; Kovalev, Sergey & Werner, Frank
(2010).
Batching for work and rework processes on dedicated facilities to minimize the makespan.
Omega. The International Journal of Management Science.
ISSN 0305-0483.
38(6),
s. 522–527.
doi:
10.1016/j.omega.2010.01.002.
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We study a planning problem of an imperfect production of a single product. The product is assumed to be continuously divisible. There are two facilities: a main facility dedicated to the original production and a facility dedicated to re-manufacturing defective units coming from the main facility. Units fabricated on the main facility are inspected for quality in batches. The quality inspection requires some time and can be performed on-line or off-line. After the inspection has been completed, defective units of the inspected batch are transported to the re-manufacturing facility. The transportation also requires some time. We assume that the fraction of the defective units is the same in each batch on the manufacturing facility and that the re-manufacturing facility is perfect. Given a demand for good quality units of the product and an upper bound K on the number of batches, the problem is to find a sequence of batch sizes such that the makespan, i.e., the time of the demand satisfaction, is minimized. We suggest a linear programming formulation, prove several properties of an optimal solution, and finally develop an O(log K) time solution algorithm. A similar per time unit cost minimization problem is studied as well.
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Hoff, Arild; Gribkovskaia, Irina; Laporte, Gilbert & Løkketangen, Arne
(2009).
Lasso solution strategies for the vehicle routing problem with pickups and deliveries.
European Journal of Operational Research.
ISSN 0377-2217.
192(3),
s. 755–766.
doi:
10.1016/j.ejor.2007.10.021.
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This paper considers the vehicle routing problem with pickups and deliveries (VRPPD) where the same customer may require both a delivery and a pickup. This is the case, for instance, of breweries that deliver beer or mineral water bottles to a set of customers and collect empty bottles from the same customers. It is possible to relax the customary practice of performing it pickup when delivering at it customer, and postpone the pickup until the vehicle has sufficient free capacity. In the case of breweries, these solutions will often consist of routes in which bottles are first delivered until the vehicle is partly unloaded, then both pickup and delivery are performed at the remaining customers, and finally empty bottles are picked Lip front the first visited customers. These customers are revisited in reverse order. thus giving rise to lasso shaped solutions. Another possibility is to relax the traditional problem even more and allow customers to be visited twice either in two different routes or at different times oil the same route, giving rise to it general solution. This article develops a tabu search algorithm capable of producing lasso solutions. A general solution can be reached by first duplicating each customer and generating a Hamiltonian solution oil the extended set of customers. Test results show that while general solutions outperform other solution shapes in term of cost. their computation cart be time consuming. The best lasso solution generated within it given time limit is generally better than the best general solution produced with the same computing effort. (c) 2007 Elsevier B.V. All rights reserved.
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Gribkovskaia, Irina; Laporte, Gilbert & Shlopak, Alexander
(2008).
A tabu search heuristic for a routing problem arising in servicing of offshore oil and gas platforms.
Journal of the Operational Research Society.
ISSN 0160-5682.
59(11),
s. 1449–1459.
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This paper introduces a pickup and delivery problem encountered in servicing of offshore oil and gas platforms in the Norwegian Sea. A single vessel must perform pickups and deliveries at several offshore platforms. All delivery demands originate at a supply base and all pickup demands are also destined to the base. The vessel capacity may never be exceeded along its route. In addition, the amount of space available for loading and unloading operations is limited at each platform. The problem, called the Single Vehicle Pickup and Delivery Problem with Capacitated Customers consists of designing a least cost vehicle (vessel) route starting and ending at the depot (base), visiting each customer (platform), and such that there is always sufficient capacity in the vehicle and at the customer location to perform the pickup and delivery operations. This paper describes several construction heuristics as well as a tabu search algorithm. Computational results are presented.
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Gribkovskaia, Irina & Laporte, Gilbert
(2008).
One-to-many-to-one single vehicle pickup and delivery problem,
The vehicle routing problem : latest advances and new challenges / Bruce Golden, S. Raghavan, Edward Wasil (eds.).
Springer.
s. 359–377.
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In One-to-Many-to-One Single Vehicle Pickup and Delivery Problems a vehicle based at the depot must make deliveries and pickups at customers locations before returning to the depot. Several variants can be defined according to the demand structures and sequencing rules imposed on pickups and deliveries. In recent years there have been an increased interest in this family of problems. New formulations and efficient heuristics capable of yielding general solutions (unrestricted in shape) have been proposed. In addition, some new and interesting extensions have been analyzed, including problems with selective pickups and problems with capacitated customers. The purpose of this chapter is to review these developments
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Gribkovskaia, Irina; Laporte, Gilbert & Shyshou, Aliaksandr
(2008).
The single vehicle routing problem with deliveries and selective pickups.
Computers & Operations Research.
ISSN 0305-0548.
35(9),
s. 2908–2924.
doi:
10.1016/j.cor.2007.01.007.
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The single vehicle routing problem with deliveries and selective pickups (SVRPDSP) is defined on a graph in which pickup and delivery demands are associated with customer vertices. The difference between this problem and the single vehicle routing problem with pickups and deliveries (SVRPPD) lies in the fact that it is no longer necessary to satisfy all pickup demands. In the SVPPDSP a pickup revenue is associated with each vertex, and the pickup demand at that vertex will be collected only if it is profitable to do so. The net cost of a route is equal to the sum of routing costs, minus the total collected revenue. The aim is to design a vehicle route of minimum net cost, visiting each customer, performing all deliveries, and a subset of the pickups. A mixed integer linear programming formulation is proposed for the SVRPDSP. Classical construction and improvement heuristics, as well as a tabu search heuristic (TS), are developed and tested on a number of instances derived from VRPLIB. Computational results show that the solutions produced by the proposed heuristics are near-optimal. There is also some evidence that the best solutions identified by the heuristics are frequently non-Hamiltonian and may contain one or two customers visited twice. (c) 2007 Elsevier Ltd. All rights reserved.
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Billaut, Jean-Charles; Gribkovskaia, Irina & Strusevich, Vitaly A.
(2008).
An improved approximation algorithm for the two-machine open shop scheduling problem with family setup times.
IIE Transactions.
ISSN 0740-817X.
40(4),
s. 478–493.
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We consider the problem of scheduling families of jobs in a two-machine open shop so as to minimize the makespan. The jobs of each family can be partitioned into batches and a family setup time on each machine is required before the first job is processed, and when a machine switches from processing a job of some family to a job of another family. For this NP-hard problem the literature contains (5/4)-approximation algorithms that cannot be improved on using the class of group technology algorithms in which each family is kept as a single batch. We demonstrate that there is no advantage in splitting a family more than once. We present an algorithm that splits one family at most once on a machine and delivers a worst-case performance ratio of 6/5.
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Berbeglia, Gerardo; Cordeau, Jean-François; Gribkovskaia, Irina & Laporte, Gilbert
(2007).
Static pickup and delivery problems: a classification scheme and survey.
TOP - An Official Journal of the Spanish Society of Statistics and Operations Research.
ISSN 1134-5764.
15(1),
s. 1–31.
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Pickup and delivery problems constitute an important class of vehicle routing problems in which objects or people have to be collected and distributed. This paper introduces a general framework to model a large collection of pickup and delivery problems, as well as a three-field classification scheme for these problems. It surveys the methods used for solving them.
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Gribkovskaia, Irina; Halskau, Øyvind & Laporte, Gilbert
(2007).
The bridges of Konigsberg - A historical perspective.
Networks: An International Journal.
ISSN 0028-3045.
49(3),
s. 199–203.
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The Bridges of Konigsberg is one of the most famous problems in graph theory. In the summer of 2005, two of the authors visited Konigsberg, now called Kaliningrad. This article provides geographical and historical information on Konigsberg and its bridges, as well as updated information on the current day situation. (c) 2007 Wiley Periodicals, Inc.
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Gribkovskaia, Irina; Halskau, Øyvind; Laporte, Gilbert & Vlcek, Martin
(2007).
General solutions to the single vehicle routing problem with pickups and deliveries.
European Journal of Operational Research.
ISSN 0377-2217.
180(2),
s. 568–584.
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The single vehicle routing problem with pickups and deliveries (SVRPPD) is defined on a graph in which pickup and delivery demands are associated with the customer vertices. The problem consists of designing a least cost route for a vehicle of capacity Q. Each customer is allowed to be visited once for a combined pickup and delivery, or twice if these two operations are performed separately. This article proposes a mixed integer linear programming model for the SVRPPD. It introduces the concept of general solution which encompasses known solution shapes such as Hamiltonian, double-path and lasso. Classical construction and improvement heuristics, as well as a tabu search heuristic, are developed and tested over several instances. Computational results show that the best solutions generated by the heuristics are frequently non-Hamiltonian and may contain up to two customers visited twice. (c) 2006 Elsevier B.V. All rights reserved.
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Aas, Bjørnar; Gribkovskaia, Irina; Halskau, Øyvind & Shlopak, Alexander
(2007).
Routing of supply vessels to petroleum installations.
International Journal of Physical Distribution & Logistics Management.
ISSN 0960-0035.
37(2),
s. 164–179.
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Purpose - In the Norwegian oil and gas industry the upstream logistics includes providing the offshore installations with needed supplies and return flow of used materials and equipment. This paper considers a real-life routing problem for supply vessels serving offshore installations at Haltenbanken off the northwest coast of Norway from its onshore supply base. The purpose of the paper is to explore how the offshore installation's limited storage capacity affects the routing of the supply vessels aiming towards creating efficient routes. Design/methodology/approach - A simplified version of the real-life routing problem for one supply vessel is formulated as a mixed integer linear programming model that contains constraints reflecting the storage requirements problem. These constraints ensure that there is enough capacity at the platform decks and that it is possible to perform both pickup and delivery services. Findings - The model has been tested on real-life-sized instances based on data provided by the Norwegian oil company Statoil ASA. The tests show that in order to obtain optimal solutions to the pickup and delivery problem with limited free storage capacities at installations, one has to include in the formulation the new sets of constraints, the storage feasibility and the service feasibility requirements. In addition, two visits to some platforms are necessary to obtain optimality. Research limitations/implications - The main limitation is the present inability to solve large cases. Originality/value - The contribution of this paper is to provide a better insight into a real-life routing problem which has a unique feature arising from the limited deck capacity at the offshore installations that complicates the performance of service. This feature has neither been discussed nor modeled in the vehicle routing literature before, hence the formulation of the problem is original and reveals some interesting results
Se alle arbeider i NVA
-
Gribkovskaia, Irina & Slettemark, Gaute Øiestad
(2024).
Tactical offshore helicopter planning.
Fulltekst i vitenarkiv
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Kovalenko, Alina; Skriabin, Anton; Strukov, Mikhail & Gribkovskaia, Irina
(2023).
Simulation modelling of transit container ship transportation with transhipment hubs via the Northeast Passage.
Fulltekst i vitenarkiv
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Kovalenko, Alina; Gribkovskaia, Irina; Skriabin, Anton & Strukov, Mikhail
(2022).
Fleet sizing for ice-capable container vessels used for the transit traffic between transhipment hubs on the Northeast Passage.
Fulltekst i vitenarkiv
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Abu-Marrul, Victor; Martinelli, Rafael; Hamacher, Silvio & Gribkovskaia, Irina
(2022).
A simulation-optimization approach for a complex parallel machine scheduling problem.
Fulltekst i vitenarkiv
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Gribkovskaia, Irina
(2022).
Multidisciplinary Norwegian-Belarusian two-diploma MSc program in Logistics Analytics: Eurasia programme project CPEA-2015/10061 (2016-2022).
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Gribkovskaia, Irina & Redutskiy, Yury
(2022).
Presentation of Norwegian-Russian collaboration project UTF-10023 Arctic Logistics.
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Skriabin, Anton; Kovalenko, Alina & Gribkovskaia, Irina
(2021).
Simulation models for fleet sizing and cargo throughput analysis in Arctic shipping.
Fulltekst i vitenarkiv
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Gribkovskaia, Irina; Stsefanovich, Kanstantsin & Pishchalava, Ahata
(2021).
Horizontal cooperation in periodic vehicle routing and periodic supply vessel planning.
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Igor, Girao Peres Vianna; Ribas, Paulo Cesar; Gribkovskaia, Irina & Filho, Virgilio Jose Martins Ferreira
(2021).
Multi-objective optimization approach for operational supply vessel planning.
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Gribkovskaia, Irina
(2021).
Norwegian-Russian collaboration project UTF-10023 Arctic Logistics: Report and Plan for 2021.
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Gribkovskaia, Irina & Bøthun, Sunniva
(2020).
Det er viktig for oss å vise vår solidaritet.
[Journal].
Romsdals Budstikke.
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Kovalenko, Alina & Gribkovskaia, Irina
(2020).
The analyses of infrastructure and transit cargoes through Arctic region.
Fulltekst i vitenarkiv
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Gribkovskaia, Irina
(2020).
Norwegian-Russian collaboration project UTF-10023 Arctic Logistics: Presentation.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2017).
Evaluation of methods for construction of robust supply vessel schedules with discrete-event simulation.
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Supply vessel planning problem arises in offshore oil and gas logistics, where a fleet of vessels provides cargo deliveries to offshore installations on a periodic basis from an onshore supply base. The objective is to define an optimal fleet composition and a least-cost weekly sailing plan of scheduled vessels' voyages. The problem is defined as a fleet-sizing and periodic routing problem with multiple time windows at installations and voyage duration constraints. Weather conditions change dynamically and may significantly influence vessels' sailing and service times, resulting in sailing plan infeasibility. The planners need vessel plans with sufficient robustness to offset the impact of weather conditions and avoid use of additional vessels. Known approaches for construction of robust vessel schedules consist of generation of shortest duration voyages and solution of a set covering model. In some approaches, voyage slacks are incorporated during voyage generation phase based on planners' experience. In other approaches, shortest generated voyages are simulated over multiple replications of wave height evolution to compute voyage robustness measure or to assign voyage duration. In this study, we evaluate robustness of vessel schedules constructed by different robustness approaches with the developed discrete-event simulation model. It simulates weekly sailing schedules repetitively over seasonal horizon over multiple replications of weather scenarios. Multi-site multivariate seasonal sea state modeling is based on nonparametric numerical resampling and intra-day hind-cast metocean data. Experiments are conducted on real-based instances from an oil and gas company. We examine the impact of various instance characteristics on robustness of weekly sailing schedules.
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Kisialiou, Yauheni & Gribkovskaia, Irina
(2017).
Heuristic based approach for generation of cost-effective and robust supply vessel schedules.
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In this work, we address the problem of supply vessel planning that arises in the upstream
offshore oil and gas logistics. Supply vessels deliver all the necessary materials
and equipment to offshore installations from an onshore supply base. Delivery takes
place according to a weekly sailing plan (delivery schedule). Charter cost of supply
vessels is the largest cost contributor in the upstream offshore supply. Therefore,
planning of supply vessels should be done so that their number is minimized and in
the same time providing reliable ow of supplies from the base not allowing for the
downtime at installations. Execution of weekly sailing plan is affected by weather
conditions, especially in the wintertime. Harsh weather conditions increase vessels
sailing and service time at installations and thus disrupt the schedule that leads to
additional costs and reduced service level. We present a developed heuristic-based
approach incorporating post-optimization simulation procedure enabling to create
cost-effective and robust vessel schedules valid for a certain season, which enhances
the possibility of generating schedules for the real large-size problem instances with
the preferred trade-offs between robustness and vessel costs.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2015).
Recourse strategies in weather dependent supply vessel operations.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2014).
Strategic fleet sizing for offshore supply vessels with stochastic service time.
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Sopot, Eugen & Gribkovskaia, Irina
(2014).
A simulation model for evaluation of supply vessel schedule robustness under demand uncertainty.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2014).
Fleet sizing for offshore supply vessels with stochastic sailing and service times.
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Gribkovskaia, Irina; Norlund, Ellen Karoline & Maisiuk, Yauhen
(2014).
Routing and fleet sizing for offshore supply vessels.
I ., . (Red.),
ROUTE 2014 : International Workshop on Vehicle Routing, Intermodal Transport and Related Areas : June 1-4, 2014.
Technical University of Denmark.
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Gribkovskaia, Irina; Norlund, Ellen Karoline & Maisiuk, Yauhen
(2014).
Routing and fleet sizing for offshore supply vessels.
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2014).
Modal split in offshore upstream supply chain under the objective of emissions minimization.
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We assess modal split in the offshore upstream supply chain of cargo
from vendors to supply bases along the Norwegian coast under the
objective of emissions minimization. To gain insight into drivers for
modal split between road and sea transport from the shipper’s perspective
a multi-period mixed integer optimization model is formulated.
The model is used to study how different demands, inventory policies
at bases and shipper commitments to sea transport affect modal split.
The results show that commitments and inventories are major drivers
towards environmental friendly sea transport.
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Kisialiou, Yauheni; Shcherbanin, Yury & Gribkovskaia, Irina
(2014).
Analysis of logistics capabilities for gas transportation in the Arctic.
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Exploration of hydrocarbons reserves in the Arctic requires development
of logistics capacities and transport infrastructure. Effect of the
global warming and year-around navigation on the Northern Sea Route
facilitate downstream transportation of gas extracted in the Arctic via
the route to Asia-Pacific markets. Using simulation model we study
the implications of the ice breaking fleet availability, climate conditions
and regulations for navigation on the route throughput. Simulation
is performed for several scenarios of LNG transportation between
different ports by different LNG carriers.
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Gribkovskaia, Irina & Norlund, Ellen Karoline
(2014).
Robust supply vessel planning with speed optimization.
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The oil and gas industry needs reliable transport of cargo between onshore
bases and offshore installations. Weather uncertainty and sailing
speed should be taken into account in supply vessel planning. To address
the problem of generating robust and green supply vessel schedules
a method combining discrete-event simulation with speed optimization
algorithms for voyage generation and applying stochastic optimization
for schedule construction is developed. Results of tests on
real instances show increased robustness and reduced emissions compared
to deterministic planning with constant speed.
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Sopot, Eugen & Gribkovskaia, Irina
(2014).
Vehicle routing problems with deliveries and pickups of multiple commodities.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2014).
Modelling of supply vessel operations with simulation.
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Supply vessel schedules are generated according to service requirements
of offshore installations characterized by cargo demand and
weekly visit frequency. Stochastic factors such as weather uncertainty
influence on the execution of schedules so that some visits are not performed.
We consider several strategies how the cargo not delivered
as planned may be shipped later. To compare the strategies and analyze
their performance a discrete-event simulation model is developed.
Tests on real data illustrate how application of these strategies for annual
horizon reduces the number of delayed visits.
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Hubin, Aliaksandr; Norlund, Ellen Karoline & Gribkovskaia, Irina
(2014).
Evaluating robustness of speed optimized supply vessel schedules.
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Offshore installations need supply vessel services on a regular basis.
Weather uncertainty impacts on how service is performed. We incorporate
different robustness and speed optimization strategies into
the two-phase optimization procedure for generation of supply vessel
schedules. To compare performance of these strategies by evaluating
robustness of generated schedules with different service parameters a
discrete-event simulation model is developed. Based on results from
simulation strategies for improving robustness incorporated into the
simulation model are applied to modify the schedules.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2013).
Fleet sizing for offshore supply vessels.
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Supply vessels provide offshore installations with necessary supplies on periodic basis from an onshore base according to weekly sailing plans. Each plan is built for
a certain time horizon to guarantee required level of service to offshore installations at least cost. In a sailing plan several voyages are assigned to each vessel. The execution of sailing plans is affected by stochastic weather conditions. A vessel may not perform all visits within the planned voyage duration because of bad weather influencing vessel's sailing and service time. In such cases, additional vessels may be needed. Deciding on the number of supply vessels to hire on the long-term basis
is an important part of the strategic fleet size planning. We present a discrete-event simulation model that evaluates alternative fleet size configurations of vessel fleet size for an annual time horizon. Keywords: Fleet Sizing, Routing, Simulation.
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Sopot, Eugen; Gribkovskaia, Irina & Laporte, Gilbert
(2012).
Routing of supply vessels to offshore installations with deliveries and pickups of multiple commodities.
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Offshore installations are dependent on periodic deliveries of various
goods from an onshore supply base and continuously generate pickup
demands. We consider the problem of routing supply vessels to offshore
installations as a multi-commodity vehicle routing problem with
pickups and deliveries. To guarantee the existence of a feasible solution
to the problem it is assumed that each installation may be visited
once or twice. We propose a variable neighborhood search heuristic
algorithm for the single vessel variant of this problem.
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2012).
Speed strategies for green supply vessel planning.
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We study how to reduce emissions in supply vessel activities through
speed optimization when planning vessel schedules by solving a MIP
model for a pre-generated set of voyages. Several speed strategies, determining
speed for the entire voyage or optimizing speed for each voyage
leg, are proposed. These strategies are applied either a priori during
voyage generation or a posterior to the voyages in the constructed schedule. Results of tests on several real-life instances show that emissions
can be significantly reduced when using speed optimization in
supply vessel planning.
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Maisiuk, Yauhen & Gribkovskaia, Irina
(2012).
A simulation study of the fleet sizing problem for offshore supply vessels.
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The supply vessels provide offshore installations with supplies from
an onshore base according to weekly sailing plans. The goal is to decide
the cost-optimal fleet of vessels on the long-term hire. The problem
is stochastic as sailing speed and service time depend on uncertain
weather conditions. Due to delays some installations may not be
served within the planned route duration, and not received supplies
have to be delivered later. We propose a discrete-event simulation
model which evaluates alternative fleet size configurations depending
on several strategies of later delivery of supplies.
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Gribkovskaia, Irina; sr, Øyvind Halskau & Qian, Fubin
(2012).
On routing and risk minimization in offshore helicopter transportation.
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Helicopters are often used for transporting crews to and from offshore
installations. Helicopter transportation is regarded as one of the main
risks in the offshore industry and the oil companies want to minimize
this risk. We show how the expected number of fatalities can be reduced
by applying different routing strategies. We present trade-offs
between the number of helicopters used and the expected risk using
real data from the Norwegian offshore industry.
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2012).
Reducing emissions in offshore supply vessel planning by speed optimization.
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Supply vessel activities, being crucial for the offshore oil and gas production, are the main source of emissions in the upstream offshore supply chain. The primary way to decrease emissions from vessels is by fuel consumption reduction. We address how to reduce fuel consumption in supply vessel activities by considering speed optimization when creating supply vessel schedules. The algorithm used for determining fleet mix and generating vessel schedules for a given time horizon consists of pre-generation of feasible voyages and packing them into vessel schedules using a set partitioning optimization model where the sum of the total vessel charter cost and the fuel cost is minimized. We propose four speed optimization strategies and show how to combine the supply vessel planning algorithm with these strategies to reduce emissions. In the first strategy, the basic solution is first found with the design vessel speed. Then, we iteratively run the algorithm with decreased speed until it generates a solution with increased fleet size, and choose the solution yielding the maximum reduction in fuel consumption compared with the basic solution. The three other strategies are speed optimization algorithms determining speed on voyage legs during voyage generation phase. One is reducing speed on a voyage leg if it is possible without violating voyage arrival times. Another is utilizing the total voyage idle time to determine the speed for each leg by rescheduling arrival times. The last is a recursive algorithm determining speed on each leg utilizing service time windows. Results of computational tests on real instances show that fuel consumption reduction can be achieved through utilization of waiting time for service and slacks in vessel schedules. The best strategy, yielding between 17% and 25% reduction in fuel consumption without an increase in the fleet size, is to optimize speed on each sailing leg.
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Qian, Fubin; Gribkovskaia, Irina; Laporte, Gilbert & sr, Øyvind Halskau
(2012).
Passenger and pilot risk minimization in offshore helicopter transportation.
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In the offshore petroleum industry, employees are transported to and from offshore installations by helicopter, which represents a major risk. We analyze how to improve transportation safety by solving the helicopter routing problem with a risk objective expressed in terms of expected number of fatalities. A mathematical model is proposed and a tabu search heuristic is applied to this problem. Three routing policies are considered: a direct routing policy, a Hamiltonian routing policy, and a general routing policy. Extensive computational experiments are conducted on instances derived from real data in order to assess and compare these policies under a travel time, a passenger risk and a combined passenger and pilot risk objective. Several management insights can be derived from this study. In particular, our results show that passenger transportation risk can be reduced by increasing travel time at the expense of pilot risk. This can be achieved through a reduction of the average number of passengers onboard by applying either a Hamiltonian or a general routing policy. Our methodology can also be used to derive an equitable distribution of risk between passengers and pilots, considering that pilots fly much more frequently than passengers. Furthermore, the helicopter routing problem is addressed as a multi-objective optimization problem. Two scenarios are considered for the cost objective. The cost objective may contain only travel time, or it is a combined travel time and service time. We apply a multi-objective genetic algorithm and an epsilon-constraint approach based on tabu search to instances derived from real data. Computational results show that the generic algorithm is capable of generating a large number of high quality solutions within reasonable times for the multi-objective helicopter routing problem. As compared to the genetic algorithm, the epsilon-constraint approach generates a small number of better quality solutions and requires more computing time.
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Qian, Fubin; Gribkovskaia, Irina; Laporte, Gilbert & sr, Øyvind Halskau
(2011).
Passenger and pilot risk minimization in offshore helicopter transportation.
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In the offshore petroleum industry, employees are transported to and from the
offshore installations by helicopter, which represents a major risk. This paper
analyzes how to improve transportation safety by solving the helicopter routing
problem with an objective expressed in terms of expected number of fatalities.
A mathematical model is proposed and a tabu search heuristic is applied to
this problem. Three routing policies are considered: a direct service policy, a
Hamiltonian solution policy, and a general solution policy.Extensive computational experiments are conducted.
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Gribkovskaia, Irina; Kurhuzava, Lidziya & Svirydava, Yuliya
(2011).
Development of routing planning tools for a distribution company.
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Gribkovskaia, Irina; Shyshou, Aliaksandr; Qian, Fubin; Laporte, Gilbert; Fagerholt, Kjetil & sr, Øyvind Halskau
(2011).
Vehicle routing problems arising in servicing offshore oil installation.
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Qian, Fubin; Gribkovskaia, Irina; Laporte, Gilbert & sr, Øyvind Halskau
(2011).
Improving transportation safety for passenger and pilot in offshore helicopter routing.
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In the offshore petroleum industry, employees are transported back and forth to the offshore installations by helicopter, which represents a major risk. A mathematical model and a tabu search heuristic are proposed to improve transportation safety by minimizing risk for passengers and pilots in terms of the expected number of fatalities in helicopter transportation. Three routing policies are implemented and compared: a direct service policy, a Hamiltonian solution policy, and a general solution policy. Computational results show that transportation risk can be reduced by using some extra flying hours, compared to the classical solutions which only consider total travel time under a Hamiltonian solution policy. Under general solution policy, low risk solutions for both passengers and pilots are obtained when minimizing the total risk. We also attempt to achieve equitable distribution of risk between passengers and pilots considering that pilots fly much more frequently than passengers.
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Shyshou, Aliaksandr; Fagerholt, Kjetil; Gribkovskaia, Irina & Laporte, Gilbert
(2010).
A large neighbourhood search heuristic for a periodic supply vessel planning problem arising in offshore oil and gas operations.
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Upstream logistics in the Norwegian oil industry includes, along with other activities, providing the offshore
installations with necessary supplies. These are periodically delivered to the installations by supply vessels
from onshore bases. This paper proposes a large neighbourhood heuristic for a real-world periodic supply vessel
planning problem faced by StatoilHydro, the largest Norwegian offshore oil and gas operator. However, the
model and the algorithm provided in the paper are of wide applicability. The problem calls for the simultaneous
determination of a repetitive weekly sailing plan and of the configuration of the supply vessel
fleet. Computational
comparisons with an exact solution method results demonstrate the competitiveness of the heuristic.
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Qian, Fubin; Gribkovskaia, Irina; Laporte, Gilbert & Halskau, Øyvind
(2010).
A tabu search heuristic for offshore helicopter routing problem with focus on passenger safety.
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A mathematical model is proposed to improve passenger transportation safety by minimizing the expected number of fatalities in offshore helicopter transportation. Tabu search heuristics are developed. Both the mathematical model and heuristics are capable of producing general solutions, namely solutions allowing a second visit to installations. Computational results show that safety performance can be significantly improved by introducing general solution strategy to helicopter routing problem.
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Qian, Fubin; Gribkovskaia, Irina & Halskau, Øyvind
(2010).
Helicopter routing in the Norwegian oil industry : including safety concerns for passenger transport.
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PURPOSE: In the Norwegian offshore oil industry, helicopters have been used as a major mode of transporting personnel to and from offshore installations for decades. Helicopter transportation represents one of the major risks for offshore employees. The purpose of this paper is to study the safety of helicopter transportation in terms of the expected number of fatalities on operational planning level. METHOD: Based on an analysis of helicopter accidents, this paper proposes a mathematical model that can aid the planning of routes for the fleet in order to minimize the expected number of fatalities. FINDINGS: A theorem proven in this paper tells that hub-and-spoke configuration is the best way of flying helicopter in terms of minimizing expected number of fatalities. Computational results indicate the expected number of fatilities may be reduced at the expence of longer travel time by implementing the proposed method into route planning for the helicopter fleet. LIMITATIONS: The main limitation is the present inability to solve large instances. IMPLICATIONS: The suggested procedure is able to provide the decision-makers with a set of solutions from which they can choose the best trade-off between travel time and transportation safety. VALUE: The mathematical model and theoretical results for route planning with a safety-based objective are original.
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Shyshou, Aliaksandr; Gribkovskaia, Irina; Fagerholt, Kjetil & Laporte, Gilbert
(2010).
Heuristic solution method for a supply vessel planning problem arising in offshore oil and gas operations.
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Shyshou, Aliaksandr; Gribkovskaia, Irina & Barceló, Jaume
(2009).
Offshore anchor handling operations : a simulation analysis of different vessel fleet configurations.
I ukjent, . (Red.),
Program and Abstracts of Optimization Days 2009, GERAD - HEC Montréal, Canada, 2009-05-04 - 2009-05-06.
GERAD Group for Research in Decision Analysis - HEC Montréal.
s. 14–14.
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We present a fleet sizing problem arising in anchor handling operations related to movement of offshore mobile units. The operations are performed by dedicated vessels, which can be hired either on the long-term or spot basis. We propose a simulation-based approach to decide the cost-optimal fleet of vessels on the long-term hire to cover future operations.
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Shyshou, Aliaksandr; Gribkovskaia, Irina & Barceló, Jaume
(2009).
A simulation model for the fleet sizing problem arising in offshore anchor handling operations.
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Gribkovskaia, Irina & Shyshou, Aliaksandr
(2009).
A simulation study of the fleet sizing problem arising in offshore anchor handling operations.
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Shyshou, Aliaksandr; Gribkovskaia, Irina & Barceló, Jaume
(2009).
A simulation model for the fleet sizing problem arising in offshore anchor handling operations.
I ., Ukjent (Red.),
Abctract CD of OYSSEUS Workshop 2009 International Workshop on Freight Transportation and Logistics, Çesme, Turkey, 2009-05-26 - 2009-05-29.
ODYSSEUS.
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Shyshou, Aliaksandr; Gribkovskaia, Irina & Barceló, Jaume
(2009).
Offshore anchor handling operations : a simulation analysis of different vessel fleet configurations.
Fulltekst i vitenarkiv
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We present a fleet sizing problem arising in anchor handling operations related to movement of offshore mobile units. The operations are performed by dedicated vessels, which can be hired either on the long-term or spot basis. We propose a simulation-based approach to decide the cost-optimal fleet of vessels on the long-term hire to cover future operations.
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Gribkovskaia, Irina & Laporte, Gilbert
(2008).
Solving a family of pickup and delivery vehicle routing problems arising in reverse logistics and the supply of oil and gas platforms,
ECCO XXI - Dubrovnik, Croatia, May 29-31. 2008 : Conference Proceedings.
Croatian Operational Research Society (HDOI).
s. 38–39.
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In one-to-many-to-one pickup and delivery single vhicle routing problems, a capacitated vehicle performs deliveries from a depot to a set of customers and also performs pickups as the same customers before returning to the depot. Several variants of the problem are considered, namely the general case, the case where customers have a limited capacity, the case where pickups are selective, the case where constraints are imposed on the lag time or sequencing order between the pickup and delivery visits at the same customer location, and the case where there are multiple commodities and time windows. Some of these variants have interesting applications in the supply of offshore oil and gas platforms and in reverse logistic. Formulating these problems as integer linear programs and solving them them by a generic solver, such as CPLEX, enables the solution of only relatively small instances. It is however possible to solve all these variants by means of a unified tabu search heuristic. In some cases, one can prove that the percentage optimally gap can be quite small. In addition, one can show that it can sometimes be advantageous to perform two separate visits at the same customer location, one for the pickup and one for the delivery, rather than performing these two operations simultaneously.
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Gribkovskaia, Irina & Laporte, Gilbert
(2008).
Solving a family of pickup and delivery vehicle routing problems arising in reverse logistics and the supply of oil and gas platforms.
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Gribkovskaia, Irina
(2007).
Single vehicle pickup and delivery problem with capacitated customers.
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The single vehicle pickup and delivery problem with capacitated customers is encountered in servicing of offshore oil and gas platforms. A single vessel must perform pickups and deliveries at several offshore platforms where all delivery demands originate at a supply base and all pickup demands are also destined to the base. The vessel capacity may never be exceeded along its route. In addition, the amount of space available for loading and unloading operations is limited at each platform. The problem consists of designing a least cost vehicle (vessel) route starting and ending at the depot (base), visiting each customer (platform) making all pickups and deliveries, and such that there is always sufficient capacity in the vehicle and at the customer location to perform the pickup and delivery operation. We present a mathematical model as well as several construction heuristics and a tabu search algorithm yielding general where any customer can be visited either once or twice.
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Gribkovskaia, Irina
(2007).
Single vehicle pickup and delivery problem with capacitated customers,
Sixth International Colloquium on Graphs and Optimization : Abstract Booklet.
Schweizerische Vereinigung für Operations Research.
s. 16–16.
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The single vehicle pickup and delivery problem with capacitated customers is encountered in servicing of offshore oil and gas platforms. A single vessel must perform pickups and deliveries at several offshore platforms where all delivery demands originate at a supply base and all pickup demands are also destined to the base. The vessel capacity may never be exceeded along its route. In addition, the amount of space available for loading and unloading operations is limited at each platform. The problem consists of designing a least cost vehicle (vessel) route starting and ending at the depot (base), visiting each customer (platform) making all pickups and deliveries, and such that there is always sufficient capacity in the vehicle and at the customer location to perform the pickup and delivery operation. We present a mathematical model as well as several construction heuristics and a tabu search algorithm yielding general where any customer can be visited either once or twice.
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Gribkovskaia, Irina & Laporte, Gilbert
(2007).
Solving a family of single vehicle pickup and delivery problems by tabu search.
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In 1-M-1 pickup and delivery single vehicle routing problem a vehicle delivers from a depot to a set of customers as well as pickups at the same customers before returning to the depot. We propose a unified tabu search heuristic for several variants of the problem: the general case, the case with customers having limited capacity, the case with selective pickups, and the case with constraints on the time-lag or sequencing order between the pickup and delivery visits at the customer location.
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Bakhrankova, Krystsina; Gribkovskaia, Irina & Haugen, Kjetil Kåre
(2007).
Production planning in continuous process industries.
I Ukjent, Ukjent (Red.),
Proceedings of the 19th Annual Conference for Nordic Researchers in Logistics, NOFOMA 2007 / Halldórsson, Á., Stefánsson, G. (Eds.) (CD-ROM).
The Nordic Logistics Research Network; NOFOMA.
s. 69–84.
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Production planning is at the core of manufacturing flow management - one of the key supply network business processes. A significant theoretical basis related to production planning for different manufacturing processes has been established in the extant literature, The classic product-process matrix has been put forward to match the product-process matrix has been put forward to match the product features with the process characteristics, distinguishing between the four types: jumbeled, disconnected line, connected line, and continuous flows. The last process type corresponds to continuous process industries that are least researched with respect to specific optimization issues. This disbalance has developed due to traditional contrasting of discrete and continuous environments without a proper differentiation between distinct process industries. In this paper we consider conceptual and optimization issues related to production planning in continuous process industries with nondiscrete products. The purpose of this paper is to locate continuous nondiscrete production within existing theoretical frameworks, discuss general features of continuous process industries and clarify their core production planning characteristics, contrasting them with other manufacturing process types. In particular, we consider a concrete example of a coninuous nondiscrete manufacturing environment to further refine its features and discuss known formalization methods applied to production planning for similar settings, assessing their potential use for the system in question. Finally, we develop a mathematical optimization model for the incumbent production system allowing a better utilization of production capacity with respect to energy costs while synchronizing production and distribution planning in the holistic supply network context.
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Bakhrankova, Krystsina; Gribkovskaia, Irina & Haugen, Kjetil Kåre
(2007).
Production planning in continuous process industries.
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Production planning is at the core of manufacturing flow management - one of the key supply network business processes. A significant theoretical basis related to production planning for different manufacturing processes has been established in the extant literature. The classic product-process matrix has been put forward to match the product features with the process characteristics, distinguishing between the four process types: jumbles, disconnected line, connected line, and continuous flows. The last process type corresponds to continuous process industries that are least researched with respect to specific optimization issues. This disbalance has developed due to traditional contrasting of discrete and continuous environments without a proper differentiation between distinct process industries. In this paper we concider conceptual and optimization issues related to production planning incontinuous process industries with nondiscrete products. The purpose of this paper is to locate continuous nondiscrete production within existing theoretical frameworks, discuss general features of continuous process industries and clarify their core production planning characteristics, contrasting them with other manufacturing process types. In particular, we consider a concrete example of a continuous nondiscrete manufacturing environment to further refine its features and discuss known formalization methods applied to production planning for similar settings, assessing their potential use for the system in question. Finally, we develop a mathematical optimization model for the incumbent production system allowing a better utilization of production capacity with respect to energy costs while synchronizing production and distribution planning in the holistic supply network context
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Gribkovskaia, Irina
(2007).
Single vehicle pickup and delivery problem with capacitated customers [ppt].
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We introduce a pickup and delivery problem encountered in the servicing of offshore oil and gas platforms in the Norwegian Sea. A single vessel must perform pickups and deliveries at several offshore platforms. All delivery demands originate at a supply base and all pickup demands are also destined to the base. The vessel capacity may never be exceeded along its route. In addition, the amount of space available for loading and unloading operations is limited at each platform. The problem, called the Single Vehicle Pickup and Delivery Problem with Capacitated Customers (SVPDPCC) consists of designing a least cost vehicle (vessel) route starting and ending at the depot (base), visiting each customer (platform), and such that there is always sufficient capacity in the vehicle and at the customer location to perform the pickup and delivery operations. A mixed integer linear programming model yielding general solutions allowing for up to two visits at customers is proposed, and the impact of the new stipulations on the solutions is analyzed. We have developed several construction heuristics as well as a tabu search algorithm. Our best heuristic consists of applying tabu search starting with an initial solution generated with construction heuristic which combines nearest neighbour, cheapest insertion and backward merging procedures. The solutions produced by our algorithm may be Hamiltonian or not, depending partly on vertex demands and relative locations.
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Gribkovskaia, Irina; Laporte, Gilbert & Shyshou, Aliaksandr
(2007).
The single vehicle routing problem with deliveries and selective pickups.
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The Single Vehicle Routing Problem with Deliveries and Selective Pickups (SVRPDSP) is defined on a graph in which n pickup and delivery demands are associated with customer vertices. In the SVRPDSP, all deliveries must be performed, but pickups are optional. The pickup demand of a customer is either fully collected, in which case it generates a revenue, or it is not collected at all. In other words, partial pickups are not allowed. The SVRPDSP consists of designing a vehicle route containing the depot and all customers, satisfying the following conditions: 1) all deliveries are performed; 2) some pickups may be performed. This definition does not specify the number of visits made at each customer. If no pickup is made, or if the pickup and the delivery are performed during the same visit, the number of visits is one, and it is two otherwise. The SVRPDSP is NP-hard since it reduces to the Traveling Salesman Problem (TSP) if none of the customers has a pickup demand and the vehicle capacity is sufficient to accommodate all the delivery demands. In the SVRPDSP a pickup revenue is associated with each vertex, and the pickup demand at that vertex will be collected only if it is profitable to do so. The net cost of a route is equal to the sum of routing costs, minus the total collected revenue. The aim is to design a vehicle route of minimum net cost, visiting each customer, performing all deliveries, and a subset of the pickups. Applications of this problem arise in reverse logistics. A mixed integer linear programming formulation, including lifted inequalities, is proposed for the SVRPDSP. Classical construction and improvement heuristics, as well as a tabu search heuristic, are developed and tested on a group of instances (with n ranging from 16 to 101) derived from VRPLIB. Extensive computational results show that the solutions produced by the proposed heuristics are near-optimal. There is also some evidence that the best solutions identified by the heuristics are frequently non-Hamiltonian and may contain one or two customers visited twice.
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Gribkovskaia, Irina
(2007).
Routing of supply vessels to offshore oil and gas platforms.
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Kovalenko, Alina; Mathisen, Terje Andreas; Gribkovskaia, Irina & Gunnarsson, Björn
(2024).
Economic feasibility of commercial transit shipping via the Northeast Passage.
Nord universitet.
ISSN 9788294093014.
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Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert
(2017).
Robust supply vessel routing and scheduling.
Høgskolen i Molde - Vitenskapelig høgskole i logistikk.
ISSN 9788279622253.
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We solve the problem of tactical supply vessel planning arising in the upstream offshore petroleum logistics. Supply vessels deliver all the necessary materials and equipment to offshore installations from an onshore supply base. Delivery takes place according to a weekly sailing plan called the vessel delivery schedule. The charter cost of supply vessels is the largest cost contributor in the upstream offshore supply. The planning of supply vessels should therefore be done so that their number is minimized and should at the same time provide reliable flow of supplies from the base. The execution of a weekly sailing plan is affected by weather conditions, especially in wintertime. Harsh weather conditions increase the number of vessels required to perform the operations as well as the service times at the installations, and thus disrupt the schedule, leading to additional costs and reduced service level. We present a metaheuristic capable of generating cost-efficient and robust vessel schedules.
Keywords: maritime logistics; supply vessel planning; vehicle routing; robust vessel schedules.
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Norlund, Ellen Karoline; Gribkovskaia, Irina & Laporte, Gilbert
(2015).
Supply vessel planning under cost, environment and robustness considerations.
Høgskolen i Molde - Vitenskapelig høgskole i logistikk.
ISSN 9788279621966.
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Offshore oil and gas installations need reliable cargo deliveries. The vessels supplying
these installations on a periodic basis are expensive and constitute a source of emissions
of greenhouse gases. Incorporating speed optimization into the supply vessel
planning process may significantly reduce fuel consumption and hence emissions. In
addition, speed optimization may yield cost reductions if the number of vessels used
does not increase. A main uncertainty factor, especially in the winter season, is the
weather conditions which impact sailing and service times. Cost minimization and the
application of speed optimization strategies may have implications on the robustness
of weekly supply vessel schedules since idle times in the schedules are reduced. We
develop a simulation-optimization based methodology that considers costs, emissions
and robustness in the generation of weekly supply vessel schedules. Results of analyses
conducted on real-based instances show that robustness requirements may yield
both increased emissions and costs in the winter season. However, depending on instance
characteristics, different degrees of robustness can be incorporated with both
costs and emissions reductions through speed optimization.
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Norlund, Ellen Karoline & Gribkovskaia, Irina
(2014).
Environmental performance of speed optimization strategies in offshore supply vessel planning under weather uncertainty.
Høgskolen i Molde - Vitenskapelig høgskole i logistikk.
ISSN 9788279621904.
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Supply vessels serving oil and gas installations at sea are a major emission source of greenhouse gases in offshore logistics. Speed optimization strategies applied in tactical vessel planning significantly reduce fuel consumption and thus emissions. Nevertheless, environmental performance of theses strategies in rough weather conditions is difficult to estimate as the duration of supply vessel operations is weather dependent. In this paper we develop a simulation-optimization tool which estimates average fuel consumption for weekly vessel schedules. The schedules are constructed by using speed optimized vessel voyages which are simulated under different weather conditions. Results of tests on real instances show that rough weather conditions increase fuel consumption and costs. Application of speed optimization strategies reduces fuel consumption both in winter and summer, but the reduction may be at the expence of a fixed vessel cost increase in the winter season
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Gribkovskaia, Irina; sr, Øyvind Halskau & Kovyalov, Mikhail Y.
(2012).
Minimizing takeoff and landing risk in helicopter pickup and delivery operations.
Høgskolen i Molde - Vitenskapelig høgskole i logistikk.
ISSN 9788279621560.
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The problem of minimizing total helicopter passenger risk caused by takeoffs and landings is
studied. There are passenger pickup and delivery demands to be satisfied at given points.
Each point is visited once. There are upper bound on the number of
flights and upper bound
on the helicopter passenger capacity. The objective function is a linear combination of the
numbers of passengers involved in takeoffs and landings at visited points. A solution is characterized by the number of
flights, sets of visited points and their sequences for all
flights.
Properties of optimal solutions are established. Several cases are proved NP-hard. A dynamic
programming algorithm is suggested for the general case. Effcient and easy for implementation algorithms are presented for the following cases: 1) a single
flight, 2) the number of visited
points not exceeding the number of
flights, and 3) an unbounded helicopter capacity, equal
risk coeffcients, and pickup demand equal to delivery demand at each point. Implementation
of the suggested solutions into the real helicopter operations should decrease the number of
fatalities in helicopter operations.
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Gribkovskaia, Irina; Kovalev, Sergey & Werner, Frank
(2009).
Lot-sizing for an imperfect continuous production on two machines.
Otto-von-Guericke-Universitat Magdeburg.
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We study the problem of planning the production of new and recovery of defective units of the same product. The product is assumed to be continuously divisible. There are a main facility dedicated to the original production and a facility dedicated to re-manufacturing defective units coming from the main facility. Units fabricated on the main facility are inspected for quality in batches. The quality inspection requires some time and can be performed on-line or off-line. After the inspection has been completed, defective units of the inspected batch are transported to the re-manufacturing facility. The transportation also requires some time. We assume that the fraction of the defective units is the same in each batch on the manufacturing facility and that the re-manufacturing facility is perfect. Given a demand for good quality units of the product and an upper bound K on the number of batches, the problem is to find a sequence of batch sizes such that the manufacturing cycle time is minimized. We suggest a linear programming formulation, prove several properties of an optimal solution, and finally develop an O(log K) time solution algorithm. A similar per time unit cost minimization problem is studied as well.
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Gribkovskaia, Irina & Laporte, Gilbert
(2007).
One-to-many-to-one single vehicle pickup and delivery problems.
GERAD - Group for Research in Decision Analysis.
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In One-to-Many-to-One Single Vehicle Pickup and Delivery Problems a vehicle based at the depot must make deliveries and pickups at customers locations before returning to the depot. Several variants can be defined according to the demand structures and sequencing rules imposed on pickups and deliveries. In recent years there has been an increased interest in this family of problems. New formulations and efficient heuristics capable of yielding general solutions (unrestricted in shape) have been proposed. In addition, some new and interesting extensions have been analyzed, including problems with selective pickups and problems with capacitated customers. The purpose of this chapter is to review these developments. Dans les problèmes de cueillette et livraison de type 'un-à-plusieurs-à-un', un véhicule basé au dépôt doit effectuer des cueillettes et livraisons chez un ensemble de clients avant de retourner au dépôt. On peut définir plusieurs variantes de ces problèmes selon la structure de la demande et les règles de séquencement imposées sur les cueillettes et les livraisons. Au cours des dernières années, on a assisté à un intérêt accru pour ces problèmes. En particulier, on a proposé de nouvelles formulations donnant lieu à des solutions dont la forme n'est pas contrainte (des solutions dites générales). De plus, plusieurs nouvelles extensions intéressantes ont été analysées, incluant des problèmes avec cueillettes sélectives ou avec clients de capacité limitée. Le but de ce chapitre est de passer ces développements en revue
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Publisert 3. sep. 2018 16:00
- Sist endret 4. apr. 2025 15:55