Gilbert Laporte

• Shaabani, Homayoun; Hvattum, Lars Magnus; Laporte, Gilbert & Hoff, Arild (2024). Stability metrics for a maritime inventory routing problem under sailing time uncertainty. EURO Journal on Transportation and Logistics. ISSN 2192-4376. 13. doi: 10.1016/j.ejtl.2024.100146. Full text in Research Archive Show summary

  We study a multi-product maritime inventory routing problem (MIRP) with sailing time uncertainty. We explicitly consider the replanning that happens after uncertainty is revealed. The objective is to determine the stability of the adjusted plans after the occurrence of an uncertain event and to evaluate the effect of incorporating different stability metrics in the rescheduling process. Five stability metrics are introduced, and mathematical formulations of the MIRP incorporating each metric are presented. A reoptimization framework is then used to analyze the impact of each stability metric. Calculations are performed using 360 instances. The main result is that adjustments to the original plan occur at no additional cost almost 50% of the time. If decision makers want a more stable plan, they should accept a 5% cost deterioration, resulting in 20% more stable solutions.

• Shaabani, Homayoun; Hvattum, Lars Magnus; Laporte, Gilbert & Hoff, Arild (2023). A goal programming model for the stability analysis of a maritime inventory routing replanning problem. Maritime Transport Research. 5(December). doi: 10.1016/j.martra.2023.100101. Full text in Research Archive
• Shaabani, Homayoun; Hoff, Arild; Hvattum, Lars Magnus & Laporte, Gilbert (2023). A matheuristic for the multi-product maritime inventory routing problem. Computers & Operations Research. ISSN 0305-0548. 154(June), p. 1–19. doi: 10.1016/j.cor.2023.106214. Full text in Research Archive Show summary

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

• Petropoulos, Fotios; Laporte, Gilbert; Aktas, Emel; Alumur, Sibel A.; Archetti, Claudia & Ayhan, Hayriye [Show all 82 contributors for this article] (2023). Operational Research : methods and applications. Journal of the Operational Research Society. ISSN 0160-5682. 75(2024)(3), p. 423–617. doi: 10.1080/01605682.2023.2253852. Full text in Research Archive
• 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), p. 411–438. doi: 10.1080/03155986.2021.1907872. Full text in Research Archive Show summary

  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

• 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), p. 305–316. doi: 10.1016/j.trc.2019.04.011. Full text in Research Archive Show summary

  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

• Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert (2018). Robust supply vessel routing and scheduling. Transportation Research Part C: Emerging Technologies. ISSN 0968-090X. 90(May), p. 366–378. doi: 10.1016/j.trc.2018.03.012. Full text in Research Archive Show summary

  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.

• 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), p. 52–64. doi: 10.1016/j.cor.2018.02.008. Full text in Research Archive Show summary

  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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• Hoff, Arild; Shaabani, Homayoun; Hvattum, Lars Magnus & Laporte, Gilbert (2023). A matheuristic for the multi-product maritime inventory routing problem. Full text in Research Archive
• Shaabani, Homayoun; Hoff, Arild; Hvattum, Lars Magnus & Laporte, Gilbert (2021). A matheuristic algorithm for maritime inventory routing problem. Full text in Research Archive
• Shaabani, Homayoun; Hvattum, Lars Magnus; Laporte, Gilbert & Hoff, Arild (2023). Stability metrics for a maritime inventory routing problem under sailing time uncertainty. Høgskolen i Molde - Vitenskapelig høgskole i logistikk. ISSN 9788279623427. Full text in Research Archive
• Kisialiou, Yauheni; Gribkovskaia, Irina & Laporte, Gilbert (2018). Supply vessel routing and scheduling under uncertain demand. Høgskolen i Molde - Vitenskapelig høgskole i logistikk. ISSN 9788279622468. Full text in Research Archive

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