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A visual interactive approach to classical and mixed vehicle routing problems with backhauls

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  • YazgI Tütüncü, G.
  • Carreto, Carlos A.C.
  • Baker, Barrie M.

Abstract

In this paper a new visual interactive approach for the classical vehicle routing problem with backhauls (VRPB) and its extensions is presented. The classical VRPB is the problem of designing minimum cost routes from a single depot to two type customers that are known as Backhaul (pickup) and Linehaul (delivery) customers where deliveries after pickups are not allowed. The mixed VRPB is an extension of the classical VRPB where deliveries after pickups are allowed. A decision support system (DSS) is developed in order to solve the classical VRPB, mixed VRPB and the restricted VRPB, which is a compromise problem between the classical VRPB, and the mixed VRPB. And a new criterion, which considers the remaining capacity of the vehicles, is proposed for producing solutions for mixed and restricted VRPB. The visual interactive approach that is based on Greedy Randomised Adaptive Memory Programming Search (GRAMPS) is described, and experimental results for the VRPB benchmark test problems are presented and analysed. The computational results on VRPB benchmark test problems indicated that the new criterion and the proposed visual interactive approach are effective towards finding a compromise between the mixed or restricted and the classical VRPB problems. The developed DSS is used by 18 students and reported to be capable of producing high quality solutions for the VRPB.

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  • YazgI Tütüncü, G. & Carreto, Carlos A.C. & Baker, Barrie M., 2009. "A visual interactive approach to classical and mixed vehicle routing problems with backhauls," Omega, Elsevier, vol. 37(1), pages 138-154, February.
  • Handle: RePEc:eee:jomega:v:37:y:2009:i:1:p:138-154
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    References listed on IDEAS

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    Cited by:

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    2. Ma, Li-Ching, 2012. "Screening alternatives graphically by an extended case-based distance approach," Omega, Elsevier, vol. 40(1), pages 96-103, January.
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    4. Wang, Hsiao-Fan & Chen, Ying-Yen, 2013. "A coevolutionary algorithm for the flexible delivery and pickup problem with time windows," International Journal of Production Economics, Elsevier, vol. 141(1), pages 4-13.
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    6. Goodwin, Paul & Fildes, Robert & Lawrence, Michael & Stephens, Greg, 2011. "Restrictiveness and guidance in support systems," Omega, Elsevier, vol. 39(3), pages 242-253, June.
    7. C. Y. Lam, 2021. "Optimizing logistics routings in a network perspective of supply and demand nodes," 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. 29(1), pages 357-377, March.
    8. Fatih Kocatürk & G. Yazgı Tütüncü & Said Salhi, 2021. "The multi-depot heterogeneous VRP with backhauls: formulation and a hybrid VNS with GRAMPS meta-heuristic approach," Annals of Operations Research, Springer, vol. 307(1), pages 277-302, December.
    9. Santos, Maria João & Curcio, Eduardo & Mulati, Mauro Henrique & Amorim, Pedro & Miyazawa, Flávio Keidi, 2020. "A robust optimization approach for the vehicle routing problem with selective backhauls," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    10. 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.
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