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A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem

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  • Lei, Chao
  • Lin, Wei-Hua
  • Miao, Lixin

Abstract

This paper considers the mobile facility routing and scheduling problem with stochastic demand (MFRSPSD). The MFRSPSD simultaneously determines the route and schedule of a fleet of mobile facilities which serve customers with uncertain demand to minimize the total cost generated during the planning horizon. The problem is formulated as a two-stage stochastic programming model, in which the first stage decision deals with the temporal and spatial movement of MFs and the second stage handles how MFs serve customer demands. An algorithm based on the multicut version of the L-shaped method is proposed in which several lower bound inequalities are developed and incorporated into the master program. The computational results show that the algorithm yields a tighter lower bound and converges faster to the optimal solution. The result of a sensitivity analysis further indicates that in dealing with stochastic demand the two-stage stochastic programming approach has a distinctive advantage over the model considering only the average demand in terms of cost reduction.

Suggested Citation

  • Lei, Chao & Lin, Wei-Hua & Miao, Lixin, 2014. "A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 699-710.
  • Handle: RePEc:eee:ejores:v:238:y:2014:i:3:p:699-710
    DOI: 10.1016/j.ejor.2014.04.024
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    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. Current, J. R. & Re Velle, C. S. & Cohon, J. L., 1985. "The maximum covering/shortest path problem: A multiobjective network design and routing formulation," European Journal of Operational Research, Elsevier, vol. 21(2), pages 189-199, August.
    3. Novoa, Clara & Storer, Robert, 2009. "An approximate dynamic programming approach for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 196(2), pages 509-515, July.
    4. George O. Wesolowsky, 1973. "Dynamic Facility Location," Management Science, INFORMS, vol. 19(11), pages 1241-1248, July.
    5. Hu, Qian & Lim, Andrew, 2014. "An iterative three-component heuristic for the team orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 232(2), pages 276-286.
    6. Tony J. Van Roy & Donald Erlenkotter, 1982. "A Dual-Based Procedure for Dynamic Facility Location," Management Science, INFORMS, vol. 28(10), pages 1091-1105, October.
    7. Ann Campbell & Michel Gendreau & Barrett Thomas, 2011. "The orienteering problem with stochastic travel and service times," Annals of Operations Research, Springer, vol. 186(1), pages 61-81, June.
    8. George O. Wesolowsky & William G. Truscott, 1975. "The Multiperiod Location-Allocation Problem with Relocation of Facilities," Management Science, INFORMS, vol. 22(1), pages 57-65, September.
    9. Vansteenwegen, Pieter & Souffriau, Wouter & Oudheusden, Dirk Van, 2011. "The orienteering problem: A survey," European Journal of Operational Research, Elsevier, vol. 209(1), pages 1-10, February.
    10. Chao, I-Ming & Golden, Bruce L. & Wasil, Edward A., 1996. "The team orienteering problem," European Journal of Operational Research, Elsevier, vol. 88(3), pages 464-474, February.
    11. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    12. C P Keller & M F Goodchild, 1988. "The multiobjective vending problem: a generalization of the travelling salesman problem," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 15(4), pages 447-460, July.
    13. Birge, John R. & Louveaux, Francois V., 1988. "A multicut algorithm for two-stage stochastic linear programs," European Journal of Operational Research, Elsevier, vol. 34(3), pages 384-392, March.
    14. António Antunes & Oded Berman & João Bigotte & Dmitry Krass, 2009. "A location model for urban hierarchy planning with population dynamics," Environment and Planning A, Pion Ltd, London, vol. 41(4), pages 996-1016, April.
    15. A. M. Geoffrion & G. W. Graves, 1974. "Multicommodity Distribution System Design by Benders Decomposition," Management Science, INFORMS, vol. 20(5), pages 822-844, January.
    16. Sonmez, Ayse Durukan & Lim, Gino J., 2012. "A decomposition approach for facility location and relocation problem with uncertain number of future facilities," European Journal of Operational Research, Elsevier, vol. 218(2), pages 327-338.
    17. Current, John R. & Schilling, David A., 1994. "The median tour and maximal covering tour problems: Formulations and heuristics," European Journal of Operational Research, Elsevier, vol. 73(1), pages 114-126, February.
    18. Labadie, Nacima & Mansini, Renata & Melechovský, Jan & Wolfler Calvo, Roberto, 2012. "The Team Orienteering Problem with Time Windows: An LP-based Granular Variable Neighborhood Search," European Journal of Operational Research, Elsevier, vol. 220(1), pages 15-27.
    19. António Antunes & Oded Berman & João Bigotte & Dmitry Krass, 2009. "A Location Model for Urban Hierarchy Planning with Population Dynamics," Environment and Planning A, , vol. 41(4), pages 996-1016, April.
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    1. repec:eee:ejores:v:268:y:2018:i:3:p:1062-1076 is not listed on IDEAS
    2. Arslan, Okan & Karaşan, Oya Ekin, 2016. "A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 670-695.

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