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Selective vehicle routing problems under uncertainty without recourse

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  • Allahviranloo, Mahdieh
  • Chow, Joseph Y.J.
  • Recker, Will W.

Abstract

We argue that the selective vehicle routing problem is more appropriate than the conventional VRP in handling uncertainty with limited resources. However, previous formulations of selective VRPs have all been deterministic. Three new formulations are proposed to account for different optimization strategies under uncertain demand (or utility) level: reliable, robust, and fuzzy selective vehicle routing problems. Three parallel genetic algorithms (PGAs) and a classic genetic algorithm are developed and compared to the deterministic solution. PGAs differ based on their communication strategies and diversity in sub-populations. Results show that a PGA, wherein communication between demes, or subpopulations, occurs in every generation and does not eliminate repeated chromosomes, outperforms other algorithms at the cost of higher computation time. A faster variation of PGA is used to solve the non-convex reliable selective VRP, robust selective VRP and the large-scale fuzzy selective VRP, consisting of 200 nodes. Large scale application demonstrates the value of fuzzy selective vehicle routing problem FSVRP in humanitarian logistics.

Suggested Citation

  • Allahviranloo, Mahdieh & Chow, Joseph Y.J. & Recker, Will W., 2014. "Selective vehicle routing problems under uncertainty without recourse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 68-88.
    • Handle: RePEc:eee:transe:v:62:y:2014:i:c:p:68-88
    DOI: 10.1016/j.tre.2013.12.004
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    as
    1. Gendreau, Michel & Laporte, Gilbert & Seguin, Rene, 1996. "Stochastic vehicle routing," European Journal of Operational Research, Elsevier, vol. 88(1), pages 3-12, January.
    2. Lam, Terence C. & Small, Kenneth A., 0. "The value of time and reliability: measurement from a value pricing experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 231-251, April.
    3. Shapiro, Arnold F., 2009. "Fuzzy random variables," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 307-314, April.
    4. Tan, K.C. & Cheong, C.Y. & Goh, C.K., 2007. "Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation," European Journal of Operational Research, Elsevier, vol. 177(2), pages 813-839, March.
    5. Dimitris J. Bertsimas & Patrick Jaillet & Amedeo R. Odoni, 1990. "A Priori Optimization," Operations Research, INFORMS, vol. 38(6), pages 1019-1033, December.
    6. Huang, Michael & Smilowitz, Karen & Balcik, Burcu, 2012. "Models for relief routing: Equity, efficiency and efficacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 2-18.
    7. Michel Gendreau & Gilbert Laporte & René Séguin, 1995. "An Exact Algorithm for the Vehicle Routing Problem with Stochastic Demands and Customers," Transportation Science, INFORMS, vol. 29(2), pages 143-155, May.
    8. Patrick Jaillet, 1988. "A Priori Solution of a Traveling Salesman Problem in Which a Random Subset of the Customers Are Visited," Operations Research, INFORMS, vol. 36(6), pages 929-936, December.
    9. Yin, Yafeng, 2008. "Robust optimal traffic signal timing," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 911-924, December.
    10. Chen, Lichun & Miller-Hooks, Elise, 2012. "Optimal team deployment in urban search and rescue," Transportation Research Part B: Methodological, Elsevier, vol. 46(8), pages 984-999.
    11. Chow, Joseph Y.J. & Regan, Amelia C., 2011. "Network-based real option models," Transportation Research Part B: Methodological, Elsevier, vol. 45(4), pages 682-695, May.
    12. Small, Kenneth A., 2001. "The Value of Pricing," University of California Transportation Center, Working Papers qt0rm449sx, University of California Transportation Center.
    13. Stewart, William R. & Golden, Bruce L., 1983. "Stochastic vehicle routing: A comprehensive approach," European Journal of Operational Research, Elsevier, vol. 14(4), pages 371-385, December.
    14. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    15. Dimitris J. Bertsimas, 1992. "A Vehicle Routing Problem with Stochastic Demand," Operations Research, INFORMS, vol. 40(3), pages 574-585, June.
    16. Holguín-Veras, José & Jaller, Miguel & Wachtendorf, Tricia, 2012. "Comparative performance of alternative humanitarian logistic structures after the Port-au-Prince earthquake: ACEs, PIEs, and CANs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1623-1640.
    17. Xu, Jiuping & Yan, Fang & Li, Steven, 2011. "Vehicle routing optimization with soft time windows in a fuzzy random environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1075-1091.
    18. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    19. Astrid S. Kenyon & David P. Morton, 2003. "Stochastic Vehicle Routing with Random Travel Times," Transportation Science, INFORMS, vol. 37(1), pages 69-82, February.
    20. Dominique Feillet & Pierre Dejax & Michel Gendreau, 2005. "Traveling Salesman Problems with Profits," Transportation Science, INFORMS, vol. 39(2), pages 188-205, May.
    21. Ghiani, Gianpaolo & Guerriero, Francesca & Laporte, Gilbert & Musmanno, Roberto, 2003. "Real-time vehicle routing: Solution concepts, algorithms and parallel computing strategies," European Journal of Operational Research, Elsevier, vol. 151(1), pages 1-11, November.
    22. Michel Gendreau & Gilbert Laporte & René Séguin, 1996. "A Tabu Search Heuristic for the Vehicle Routing Problem with Stochastic Demands and Customers," Operations Research, INFORMS, vol. 44(3), pages 469-477, June.
    23. Gilbert Laporte & FranÇois V. Louveaux & Luc van Hamme, 2002. "An Integer L -Shaped Algorithm for the Capacitated Vehicle Routing Problem with Stochastic Demands," Operations Research, INFORMS, vol. 50(3), pages 415-423, June.
    24. Joseph Y. J. Chow & Amelia C. Regan, 2011. "Real Option Pricing of Network Design Investments," Transportation Science, INFORMS, vol. 45(1), pages 50-63, February.
    25. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    26. Recker, W. W., 1995. "The household activity pattern problem: General formulation and solution," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 61-77, February.
    27. Li Ping Gan & Will Recker, 2013. "Stochastic Preplanned Household Activity Pattern Problem with Uncertain Activity Participation (SHAPP)," Transportation Science, INFORMS, vol. 47(3), pages 439-454, August.
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