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Heuristics for the multi-depot petrol station replenishment problem with time windows

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  • Cornillier, Fabien
  • Boctor, Fayez
  • Renaud, Jacques

Abstract

In the multi-depot petrol station replenishment problem with time windows (MPSRPTW), the delivery of petroleum products stored in a number of different petroleum depots to a set of petrol distribution stations has to be optimized. Each depot has its own fleet of heterogeneous and compartmented tank trucks. Stations specify their demand by indicating the minimum and maximum quantities to be delivered for each ordered product and require the delivery within a predetermined time window. Several inter-related decisions must be made simultaneously in order to solve the problem. For this problem, the set of feasible routes to deliver all the demands, the departure depot for each route, the quantities of each product to be delivered, the assignment of these routes to trucks, the time schedule for each trip, and the loading of the ordered products to different tanks of the trucks used need to be determined. In this paper, we propose a mathematical model that selects, among a set of feasible trips, the subset that allows the delivery of all the demands while maximizing the overall daily net revenue. If this model is provided with all possible feasible trips, it determines the optimal solution for the corresponding MPSRPTW. However, since the number of such trips is often huge, we developed a procedure to generate a restricted set of promising feasible trips. Using this restricted set, the model produces a good but not necessarily optimal solution. Thus the proposed solution process can be seen as a heuristic. We report the results of the extensive numerical tests carried out to assess the performance of the proposed heuristic. In addition, we show that, for the special case of only one depot, the proposed heuristic outperforms a previously published solution method.

Suggested Citation

  • Cornillier, Fabien & Boctor, Fayez & Renaud, Jacques, 2012. "Heuristics for the multi-depot petrol station replenishment problem with time windows," European Journal of Operational Research, Elsevier, vol. 220(2), pages 361-369.
  • Handle: RePEc:eee:ejores:v:220:y:2012:i:2:p:361-369
    DOI: 10.1016/j.ejor.2012.02.007
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    References listed on IDEAS

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    3. Yan Cheng Hsu & Jose L. Walteros & Rajan Batta, 2020. "Solving the petroleum replenishment and routing problem with variable demands and time windows," Annals of Operations Research, Springer, vol. 294(1), pages 9-46, November.
    4. Li, Kunpeng & Chen, Bin & Sivakumar, Appa Iyer & Wu, Yong, 2014. "An inventory–routing problem with the objective of travel time minimization," European Journal of Operational Research, Elsevier, vol. 236(3), pages 936-945.
    5. Pasquale Carotenuto & Stefano Giordani & Alessio Salvatore, 2024. "A Matheuristic Approach for the Multi-Depot Periodic Petrol Station Replenishment Problem," Mathematics, MDPI, vol. 12(3), pages 1-19, January.
    6. Lahyani, Rahma & Coelho, Leandro C. & Khemakhem, Mahdi & Laporte, Gilbert & Semet, Frédéric, 2015. "A multi-compartment vehicle routing problem arising in the collection of olive oil in Tunisia," Omega, Elsevier, vol. 51(C), pages 1-10.
    7. Ana Moura & Telmo Pinto & Cláudio Alves & José Valério de Carvalho, 2023. "A Matheuristic Approach to the Integration of Three-Dimensional Bin Packing Problem and Vehicle Routing Problem with Simultaneous Delivery and Pickup," Mathematics, MDPI, vol. 11(3), pages 1-16, January.
    8. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2016. "Vehicle routing problems with multiple trips," 4OR, Springer, vol. 14(3), pages 223-259, September.
    9. Hiba Yahyaoui & Islem Kaabachi & Saoussen Krichen & Abdulkader Dekdouk, 2020. "Two metaheuristic approaches for solving the multi-compartment vehicle routing problem," Operational Research, Springer, vol. 20(4), pages 2085-2108, December.
    10. Li, Yanfeng & Szeto, W.Y. & Long, Jiancheng & Shui, C.S., 2016. "A multiple type bike repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 263-278.
    11. Songyi Wang & Fengming Tao & Yuhe Shi, 2018. "Optimization of Inventory Routing Problem in Refined Oil Logistics with the Perspective of Carbon Tax," Energies, MDPI, vol. 11(6), pages 1-17, June.
    12. Coelho, Leandro C. & Laporte, Gilbert, 2015. "Classification, models and exact algorithms for multi-compartment delivery problems," European Journal of Operational Research, Elsevier, vol. 242(3), pages 854-864.
    13. Sun, Lijun & Zhang, Yuankai & Hu, Xiangpei, 2021. "Economical-traveling-distance-based fleet composition with fuel costs: An application in petrol distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    14. Vélez-Gallego, Mario C. & Teran-Somohano, Alejandro & Smith, Alice E., 2020. "Minimizing late deliveries in a truck loading problem," European Journal of Operational Research, Elsevier, vol. 286(3), pages 919-928.
    15. Bani, Abderrahman & El Hallaoui, Issmail & Corréa, Ayoub Insa & Tahir, Adil, 2023. "Solving a real-world multi-depot multi-period petrol replenishment problem with complex loading constraints," European Journal of Operational Research, Elsevier, vol. 311(1), pages 154-172.
    16. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    17. Nasr Al-Hinai & Chefi Triki, 2020. "A two-level evolutionary algorithm for solving the petrol station replenishment problem with periodicity constraints and service choice," Annals of Operations Research, Springer, vol. 286(1), pages 325-350, March.
    18. Du, Jia Yan & Brunner, Jens O. & Kolisch, Rainer, 2014. "Planning towing processes at airports more efficiently," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 293-304.

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