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A face search heuristic algorithm for optimizing over the efficient set

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  • Harold P. Benson
  • Serpil Sayin

Abstract

The problem of optimizing a linear function over the efficient set of a multiple objective linear program is an important but difficult problem in multiple criteria decision making. In this article we present a flexible face search heuristic algorithm for the problem. Preliminary computational experiments indicate that the algorithm gives very good estimates of the global optimum with relatively little computational effort. © 1993 John Wiley & Sons, Inc.

Suggested Citation

  • Harold P. Benson & Serpil Sayin, 1993. "A face search heuristic algorithm for optimizing over the efficient set," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(1), pages 103-116, February.
  • Handle: RePEc:wly:navres:v:40:y:1993:i:1:p:103-116
    DOI: 10.1002/1520-6750(199302)40:13.0.CO;2-A
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    References listed on IDEAS

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    1. Odile Marcotte & Richard M. Soland, 1986. "An Interactive Branch-and-Bound Algorithm for Multiple Criteria Optimization," Management Science, INFORMS, vol. 32(1), pages 61-75, January.
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    Cited by:

    1. Tu, Ta Van, 2000. "Optimization over the efficient set of a parametric multiple objective linear programming problem," European Journal of Operational Research, Elsevier, vol. 122(3), pages 570-583, May.
    2. Serpil Sayin, 2003. "A Procedure to Find Discrete Representations of the Efficient Set with Specified Coverage Errors," Operations Research, INFORMS, vol. 51(3), pages 427-436, June.
    3. Serpil Sayin, 2000. "Optimizing Over the Efficient Set Using a Top-Down Search of Faces," Operations Research, INFORMS, vol. 48(1), pages 65-72, February.
    4. Stacey Faulkenberg & Margaret Wiecek, 2012. "Generating equidistant representations in biobjective programming," Computational Optimization and Applications, Springer, vol. 51(3), pages 1173-1210, April.
    5. Daniel Jornada & V. Jorge Leon, 2020. "Filtering Algorithms for Biobjective Mixed Binary Linear Optimization Problems with a Multiple-Choice Constraint," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 57-73, January.

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