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Adaptive Path Relinking for Vehicle Routing and Scheduling Problems with Product Returns

Author

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  • Christos D. Tarantilis

    (Operations Research and Decision Systems Centre, Management Science Laboratory, Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece GR 10434)

  • Afroditi K. Anagnostopoulou

    (Operations Research and Decision Systems Centre, Management Science Laboratory, Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece GR 10434)

  • Panagiotis P. Repoussis

    (Howe School of Technology Management, Stevens Institute of Technology, Hoboken, New Jersey 07030)

Abstract

This paper deals with one-to-many-to-one vehicle routing and scheduling problems with pickups and deliveries and studies the effect of various backhauling strategies. Initially, focus is given on problem instances with clustered backhauls where all delivery customers must be visited before pickup customers. Afterward, operational settings with mixed backhauls and varying visiting sequence restrictions with respect to the capacity of the vehicles are examined. The proposed solution method evolves a set of reference solutions on the basis of a novel Adaptive Path Relinking framework. The latter encompasses an adaptive multisolution recombination procedure to generate provisional solutions based on the recurrence of particular solution attributes. On return, these solutions are used as guiding points for performing search trajectories from initial reference solutions via tunneling. Computational results on benchmark data sets of the literature illustrate the competitiveness and robustness of the proposed approach compared to state-of-the-art solution methods for well-known vehicle routing and scheduling problems. Finally, various experiments are also reported to demonstrate the economic effect of different mixing levels and densities of linehaul and backhaul customers.

Suggested Citation

  • Christos D. Tarantilis & Afroditi K. Anagnostopoulou & Panagiotis P. Repoussis, 2013. "Adaptive Path Relinking for Vehicle Routing and Scheduling Problems with Product Returns," Transportation Science, INFORMS, vol. 47(3), pages 356-379, August.
  • Handle: RePEc:inm:ortrsc:v:47:y:2013:i:3:p:356-379
    DOI: 10.1287/trsc.1120.0439
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    References listed on IDEAS

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    4. Schneider, Michael & Schwahn, Fabian & Vigo, Daniele, 2017. "Designing granular solution methods for routing problems with time windows," European Journal of Operational Research, Elsevier, vol. 263(2), pages 493-509.
    5. Fang, Chao & Han, Zonglei & Wang, Wei & Zio, Enrico, 2023. "Routing UAVs in landslides Monitoring: A neural network heuristic for team orienteering with mandatory visits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    6. Schaumann, Sarah K. & Bergmann, Felix M. & Wagner, Stephan M. & Winkenbach, Matthias, 2023. "Route efficiency implications of time windows and vehicle capacities in first- and last-mile logistics," European Journal of Operational Research, Elsevier, vol. 311(1), pages 88-111.
    7. 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.
    8. 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.
    9. Queiroga, Eduardo & Frota, Yuri & Sadykov, Ruslan & Subramanian, Anand & Uchoa, Eduardo & Vidal, Thibaut, 2020. "On the exact solution of vehicle routing problems with backhauls," European Journal of Operational Research, Elsevier, vol. 287(1), pages 76-89.
    10. Amalia I. Nikolopoulou & Panagiotis P. Repoussis & Christos D. Tarantilis & Emmanouil E. Zachariadis, 2019. "Adaptive memory programming for the many-to-many vehicle routing problem with cross-docking," Operational Research, Springer, vol. 19(1), pages 1-38, March.
    11. Gábor Nagy & Niaz A. Wassan & M. Grazia Speranza & Claudia Archetti, 2015. "The Vehicle Routing Problem with Divisible Deliveries and Pickups," Transportation Science, INFORMS, vol. 49(2), pages 271-294, May.
    12. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    13. Xia, Yang & Zeng, Wenjia & Zhang, Canrong & Yang, Hai, 2023. "A branch-and-price-and-cut algorithm for the vehicle routing problem with load-dependent drones," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 80-110.
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