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An arc-exchange decomposition method for multistage dynamic networks with random arc capacities

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  • Song, Haiqing
  • Cheung, Raymond K.
  • Wang, Haiyan

Abstract

Multistage dynamic networks with random arc capacities (MDNRAC) have been successfully used for modeling various resource allocation problems in the transportation area. However, solving these problems is generally computationally intensive, and there is still a need to develop more efficient solution approaches. In this paper, we propose a new heuristic approach that solves the MDNRAC problem by decomposing the network at each stage into a series of subproblems with tree structures. Each subproblem can be solved efficiently. The main advantage is that this approach provides an efficient computational device to handle the large-scale problem instances with fairly good solution quality. We show that the objective value obtained from this decomposition approach is an upper bound for that of the MDNRAC problem. Numerical results demonstrate that our proposed approach works very well.

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  • Song, Haiqing & Cheung, Raymond K. & Wang, Haiyan, 2014. "An arc-exchange decomposition method for multistage dynamic networks with random arc capacities," European Journal of Operational Research, Elsevier, vol. 233(3), pages 474-487.
  • Handle: RePEc:eee:ejores:v:233:y:2014:i:3:p:474-487
    DOI: 10.1016/j.ejor.2013.09.048
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    1. Julia L. Higle & Wing W. Lowe & Ronald Odio, 1994. "Conditional Stochastic Decomposition: An Algorithmic Interface for Optimization and Simulation," Operations Research, INFORMS, vol. 42(2), pages 311-322, April.
    2. N. C. P. Edirisinghe & W. T. Ziemba, 1994. "Bounds for Two-Stage Stochastic Programs with Fixed Recourse," Mathematics of Operations Research, INFORMS, vol. 19(2), pages 292-313, May.
    3. Raymond K. Cheung & Chuen-Yih Chen, 1998. "A Two-Stage Stochastic Network Model and Solution Methods for the Dynamic Empty Container Allocation Problem," Transportation Science, INFORMS, vol. 32(2), pages 142-162, May.
    4. András Prékopa, 1999. "The use of discrete moment bounds in probabilisticconstrained stochastic programming models," Annals of Operations Research, Springer, vol. 85(0), pages 21-38, January.
    5. Warren B. Powell & Abraham George & Hugo Simão & Warren Scott & Alan Lamont & Jeffrey Stewart, 2012. "SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology, and Policy," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 665-682, November.
    6. Gregory A. Godfrey & Warren B. Powell, 2002. "An Adaptive Dynamic Programming Algorithm for Dynamic Fleet Management, I: Single Period Travel Times," Transportation Science, INFORMS, vol. 36(1), pages 21-39, February.
    7. Raymond K. Cheung & Warren B. Powell, 1996. "An Algorithm for Multistage Dynamic Networks with Random Arc Capacities, with an Application to Dynamic Fleet Management," Operations Research, INFORMS, vol. 44(6), pages 951-963, December.
    8. Astrid S. Kenyon & David P. Morton, 2003. "Stochastic Vehicle Routing with Random Travel Times," Transportation Science, INFORMS, vol. 37(1), pages 69-82, February.
    9. Song, Haiqing & Huang, Huei-Chuen, 2008. "A successive convex approximation method for multistage workforce capacity planning problem with turnover," European Journal of Operational Research, Elsevier, vol. 188(1), pages 29-48, July.
    10. N. C. P. Edirisinghe & W. T. Ziemba, 1992. "Tight Bounds for Stochastic Convex Programs," Operations Research, INFORMS, vol. 40(4), pages 660-677, August.
    11. Kouwenberg, Roy, 2001. "Scenario generation and stochastic programming models for asset liability management," European Journal of Operational Research, Elsevier, vol. 134(2), pages 279-292, October.
    12. Gregory D. Glockner & George L. Nemhauser, 2000. "A Dynamic Network Flow Problem with Uncertain arc Capacities: Formulation and Problem Structure," Operations Research, INFORMS, vol. 48(2), pages 233-242, April.
    13. Linos F. Frantzeskakis & Warren B. Powell, 1990. "A Successive Linear Approximation Procedure for Stochastic, Dynamic Vehicle Allocation Problems," Transportation Science, INFORMS, vol. 24(1), pages 40-57, February.
    14. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    15. Julia L. Higle & Suvrajeet Sen, 1991. "Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse," Mathematics of Operations Research, INFORMS, vol. 16(3), pages 650-669, August.
    16. Hugo P. Simão & Abraham George & Warren B. Powell & Ted Gifford & John Nienow & Jeff Day, 2010. "Approximate Dynamic Programming Captures Fleet Operations for Schneider National," Interfaces, INFORMS, vol. 40(5), pages 342-352, October.
    17. 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.
    18. Warren B. Powell & Linos F. Frantzeskakis, 1994. "Restricted Recourse Strategies for Dynamic Networks with Random Arc Capacities," Transportation Science, INFORMS, vol. 28(1), pages 3-23, February.
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