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Interactive Coordination of Objective Decompositions in Multiobjective Programming

Author

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  • Alexander Engau

    (Department of Management Sciences, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada)

  • Margaret M. Wiecek

    (Department of Mathematical Sciences, Clemson University, Clemson, South Carolina 29634)

Abstract

To remedy challenges resulting from a high number of objectives in multiobjective programming and multicriteria decision making, this paper chooses to decompose the vector objective function and characterizes the relationships between solutions for the original problem and the collection of decomposed subproblems. In particular, it is shown how solutions that are found using this decomposition approach relate to solutions found by traditional scalarization techniques. For the selection of a final solution, two interactive coordination methods are proposed that allow to find any solution for the original problem by merely solving the smaller-sized subproblems, while integrating both preferences of the decision maker and trade-off information obtained from a sensitivity analysis. A theoretical foundation for the procedures is established, and their application is illustrated for portfolio optimization and a design selection problem.

Suggested Citation

  • Alexander Engau & Margaret M. Wiecek, 2008. "Interactive Coordination of Objective Decompositions in Multiobjective Programming," Management Science, INFORMS, vol. 54(7), pages 1350-1363, July.
    • Handle: RePEc:inm:ormnsc:v:54:y:2008:i:7:p:1350-1363
    DOI: 10.1287/mnsc.1070.0848
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    References listed on IDEAS

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    Cited by:

    1. Dranichak, Garrett M. & Wiecek, Margaret M., 2019. "On highly robust efficient solutions to uncertain multiobjective linear programs," European Journal of Operational Research, Elsevier, vol. 273(1), pages 20-30.
    2. Alzorba, Shaghaf & Günther, Christian & Popovici, Nicolae & Tammer, Christiane, 2017. "A new algorithm for solving planar multiobjective location problems involving the Manhattan norm," European Journal of Operational Research, Elsevier, vol. 258(1), pages 35-46.
    3. Sauli Ruuska & Kaisa Miettinen & Margaret M. Wiecek, 2012. "Connections Between Single-Level and Bilevel Multiobjective Optimization," Journal of Optimization Theory and Applications, Springer, vol. 153(1), pages 60-74, April.
    4. Jornada, Daniel & Leon, V. Jorge, 2016. "Biobjective robust optimization over the efficient set for Pareto set reduction," European Journal of Operational Research, Elsevier, vol. 252(2), pages 573-586.
    5. Melissa Gardenghi & Trinidad Gómez & Francisca Miguel & Margaret M. Wiecek, 2011. "Algebra of Efficient Sets for Multiobjective Complex Systems," Journal of Optimization Theory and Applications, Springer, vol. 149(2), pages 385-410, May.
    6. Engau, Alexander, 2009. "Tradeoff-based decomposition and decision-making in multiobjective programming," European Journal of Operational Research, Elsevier, vol. 199(3), pages 883-891, December.
    7. Boland, Natashia & Charkhgard, Hadi & Savelsbergh, Martin, 2019. "Preprocessing and cut generation techniques for multi-objective binary programming," European Journal of Operational Research, Elsevier, vol. 274(3), pages 858-875.

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