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Revised-Modified Penalties for Fixed Charge Transportation Problems

Author

Listed:
  • Bruce W. Lamar

    (MITRE Corporation, Bedford, Massachusetts 01730)

  • Chris A. Wallace

    (University of Auckland, Auckland, New Zealand)

Abstract

Conditional penalties are used to obtain lower bounds to subproblems in a branch-and-bound procedure that can be tighter than the LP relaxation of the subproblems. For the fixed charge transportation problem (FCTP), branch-and-bound algorithms have been implemented using conditional penalties proposed by Driebeek (Driebeek, N. 1966. An algorithm for the solution of mixed integer programming problems. Management Sci. 12 576--587.), Cabot and Erenguc (Cabot, A. V., S. S. Erenguc. 1984. Some branch-and-bound procedures for fixed-cost transportation problems. Naval Res. Logistics 31 145--154.), and Palekar et al. (Palekar, V. S., M. H. Karwan, S. Zionts. 1990. A branch-and-bound method for the fixed charge transportation problem. Management Sci. 36 1092--1105.). The last conditional penalties are referred to as the "modified" penalties. In this paper, we show that the modified penalties are not valid conditional penalties. In fact, in nearly a quarter of the test problems examined, the modified penalties prevented the branch-and-bound algorithm from properly identifying the optimal solution to the FCTP. A simple change, which corrects a subcase in the penalty calculation, restores the validity of the modified penalties while retaining their efficiency. Computational tests indicate that the "revised-modified" penalties continue to dominate the Driebeek and the Cabot and Erenguc penalties.

Suggested Citation

  • Bruce W. Lamar & Chris A. Wallace, 1997. "Revised-Modified Penalties for Fixed Charge Transportation Problems," Management Science, INFORMS, vol. 43(10), pages 1431-1436, October.
    • Handle: RePEc:inm:ormnsc:v:43:y:1997:i:10:p:1431-1436
    DOI: 10.1287/mnsc.43.10.1431
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    Citations

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    Cited by:

    1. Sun, Minghe, 2002. "The transportation problem with exclusionary side constraints and two branch-and-bound algorithms," European Journal of Operational Research, Elsevier, vol. 140(3), pages 629-647, August.
    2. Jesús Sáez Aguado, 2009. "Fixed Charge Transportation Problems: a new heuristic approach based on Lagrangean relaxation and the solving of core problems," Annals of Operations Research, Springer, vol. 172(1), pages 45-69, November.
    3. Yogesh Agarwal & Yash Aneja, 2012. "Fixed-Charge Transportation Problem: Facets of the Projection Polyhedron," Operations Research, INFORMS, vol. 60(3), pages 638-654, June.
    4. Francesca Maggioni & Michal Kaut & Luca Bertazzi, 2009. "Stochastic optimization models for a single-sink transportation problem," Computational Management Science, Springer, vol. 6(2), pages 251-267, May.
    5. Jeffery L. Kennington & Charles D. Nicholson, 2010. "The Uncapacitated Time-Space Fixed-Charge Network Flow Problem: An Empirical Investigation of Procedures for Arc Capacity Assignment," INFORMS Journal on Computing, INFORMS, vol. 22(2), pages 326-337, May.
    6. Gavin J. Bell & Bruce W. Lamar & Chris A. Wallace, 1999. "Capacity improvement, penalties, and the fixed charge transportation problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(4), pages 341-355, June.
    7. Dimitri J. Papageorgiou & Alejandro Toriello & George L. Nemhauser & Martin W. P. Savelsbergh, 2012. "Fixed-Charge Transportation with Product Blending," Transportation Science, INFORMS, vol. 46(2), pages 281-295, May.
    8. Erika Buson & Roberto Roberti & Paolo Toth, 2014. "A Reduced-Cost Iterated Local Search Heuristic for the Fixed-Charge Transportation Problem," Operations Research, INFORMS, vol. 62(5), pages 1095-1106, October.
    9. Jawahar, N. & Balaji, A.N., 2009. "A genetic algorithm for the two-stage supply chain distribution problem associated with a fixed charge," European Journal of Operational Research, Elsevier, vol. 194(2), pages 496-537, April.
    10. Roberto Roberti & Enrico Bartolini & Aristide Mingozzi, 2015. "The Fixed Charge Transportation Problem: An Exact Algorithm Based on a New Integer Programming Formulation," Management Science, INFORMS, vol. 61(6), pages 1275-1291, June.
    11. Francesca Maggioni & Florian A. Potra & Marida Bertocchi, 2017. "A scenario-based framework for supply planning under uncertainty: stochastic programming versus robust optimization approaches," Computational Management Science, Springer, vol. 14(1), pages 5-44, January.

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