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The cumulative capacitated vehicle routing problem with min-sum and min-max objectives: An effective hybridisation of adaptive variable neighbourhood search and large neighbourhood search

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  • Sze, Jeeu Fong
  • Salhi, Said
  • Wassan, Niaz

Abstract

The cumulative capacitated vehicle routing problem (CCVRP) is a relatively new variant of the classical capacitated vehicle routing problem in which the objective is to minimise the sum of arrival times at customers (min-sum) instead of the total route distance. While the literature for the CCVRP is scarce, this problem has useful applications especially in the area of supplying humanitarian aid after a natural disaster. In this paper, a two-stage adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed. When tested on the benchmark data sets, the results show that the proposed AVNS is highly competitive in producing new best known solutions to more than half of the instances. An alternative but related objective that minimises the maximum arrival time (min-max) is also explored in this study demonstrating the flexibility and the effectiveness of the proposed metaheuristic. To the best of our knowledge, this is the first study that exploits the min-max objective of the CCVRP in addition to providing extensive computational results for a large number of instances for the min-sum. As a by-product of this study, managerial insights for decision making are also presented.

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  • Sze, Jeeu Fong & Salhi, Said & Wassan, Niaz, 2017. "The cumulative capacitated vehicle routing problem with min-sum and min-max objectives: An effective hybridisation of adaptive variable neighbourhood search and large neighbourhood search," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 162-184.
    • Handle: RePEc:eee:transb:v:101:y:2017:i:c:p:162-184
    DOI: 10.1016/j.trb.2017.04.003
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    1. Iris Martínez-Salazar & Francisco Angel-Bello & Ada Alvarez, 2015. "A customer-centric routing problem with multiple trips of a single vehicle," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(8), pages 1312-1323, August.
    2. Andreas Stenger & Daniele Vigo & Steffen Enz & Michael Schwind, 2013. "An Adaptive Variable Neighborhood Search Algorithm for a Vehicle Routing Problem Arising in Small Package Shipping," Transportation Science, INFORMS, vol. 47(1), pages 64-80, February.
    3. 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.
    4. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2014. "A unified solution framework for multi-attribute vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 234(3), pages 658-673.
    5. Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Chris T., 2015. "The load-dependent vehicle routing problem and its pick-up and delivery extension," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 158-181.
    6. Salhi, S. & Sari, M., 1997. "A multi-level composite heuristic for the multi-depot vehicle fleet mix problem," European Journal of Operational Research, Elsevier, vol. 103(1), pages 95-112, November.
    7. Juan Rivera & H. Afsar & Christian Prins, 2015. "A multistart iterated local search for the multitrip cumulative capacitated vehicle routing problem," Computational Optimization and Applications, Springer, vol. 61(1), pages 159-187, May.
    8. Ann Melissa Campbell & Dieter Vandenbussche & William Hermann, 2008. "Routing for Relief Efforts," Transportation Science, INFORMS, vol. 42(2), pages 127-145, May.
    9. López-Sánchez, A.D. & Hernández-Díaz, A.G. & Vigo, D. & Caballero, R. & Molina, J., 2014. "A multi-start algorithm for a balanced real-world Open Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 238(1), pages 104-113.
    10. Richard Hartl & Geir Hasle & Gerrit Janssens, 2006. "Special issue on Rich Vehicle Routing Problems," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(2), pages 103-104, June.
    11. Lysgaard, Jens & Wøhlk, Sanne, 2014. "A branch-and-cut-and-price algorithm for the cumulative capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 800-810.
    12. Marshall L. Fisher, 1994. "Optimal Solution of Vehicle Routing Problems Using Minimum K-Trees," Operations Research, INFORMS, vol. 42(4), pages 626-642, August.
    13. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    14. Elshaikh, Abdalla & Salhi, Said & Nagy, Gábor, 2015. "The continuous p-centre problem: An investigation into variable neighbourhood search with memory," European Journal of Operational Research, Elsevier, vol. 241(3), pages 606-621.
    15. Luo, Zhixing & Qin, Hu & Lim, Andrew, 2014. "Branch-and-price-and-cut for the multiple traveling repairman problem with distance constraints," European Journal of Operational Research, Elsevier, vol. 234(1), pages 49-60.
    16. Silva, Marcos Melo & Subramanian, Anand & Vidal, Thibaut & Ochi, Luiz Satoru, 2012. "A simple and effective metaheuristic for the Minimum Latency Problem," European Journal of Operational Research, Elsevier, vol. 221(3), pages 513-520.
    17. Rivera, Juan Carlos & Murat Afsar, H. & Prins, Christian, 2016. "Mathematical formulations and exact algorithm for the multitrip cumulative capacitated single-vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 249(1), pages 93-104.
    18. A Corberán & E Fernández & M Laguna & R Martí, 2002. "Heuristic solutions to the problem of routing school buses with multiple objectives," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 427-435, April.
    19. Park, Junhyuk & Kim, Byung-In, 2010. "The school bus routing problem: A review," European Journal of Operational Research, Elsevier, vol. 202(2), pages 311-319, April.
    20. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The impact of depot location, fleet composition and routing on emissions in city logistics," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 81-102.
    21. Hof, Julian & Schneider, Michael & Goeke, Dominik, 2017. "Solving the battery swap station location-routing problem with capacitated electric vehicles using an AVNS algorithm for vehicle-routing problems with intermediate stops," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 102-112.
    22. Bowerman, Robert & Hall, Brent & Calamai, Paul, 1995. "A multi-objective optimization approach to urban school bus routing: Formulation and solution method," Transportation Research Part A: Policy and Practice, Elsevier, vol. 29(2), pages 107-123, March.
    23. Goel, Asvin & Gruhn, Volker, 2008. "A General Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 191(3), pages 650-660, December.
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