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Relative importance of criteria in multiobjective programming: A cone-based approach

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  • Hunt, Brian J.
  • Wiecek, Margaret M.
  • Hughes, Colleen S.

Abstract

This article develops a convex polyhedral cone-based preference modeling framework for decision making with multiple criteria which extends the classical notion of Pareto optimality and accounts for relative importance of the criteria. The decision maker's perception of the relative importance is quantified by an allowable tradeoffs between two objectives representing the maximum allowable amount of decay of a less important objective per one unit of improvement of a more important objective. Two cone-based models of relative importance are developed. In the first model, one criterion is designated as less important while all the others are more important. In the second model, more than one criterion may be classified as less important while all the others are considered more important. Complete algebraic characterization of the models is derived and the relationship between them and the classical Pareto preference is examined. Their relevance to decision making is discussed.

Suggested Citation

  • Hunt, Brian J. & Wiecek, Margaret M. & Hughes, Colleen S., 2010. "Relative importance of criteria in multiobjective programming: A cone-based approach," European Journal of Operational Research, Elsevier, vol. 207(2), pages 936-945, December.
  • Handle: RePEc:eee:ejores:v:207:y:2010:i:2:p:936-945
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    References listed on IDEAS

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    1. Christophe Labreuche & M. Grabisch, 2007. "The representation of conditional relative importance between criteria," Annals of Operations Research, Springer, vol. 154(1), pages 93-122, October.
    2. Podinovski, Vladislav V., 2007. "Interval articulation of superiority and precise elicitation of priorities," European Journal of Operational Research, Elsevier, vol. 180(1), pages 406-417, July.
    3. Margaret M. Wiecek & Vincent Y. Blouin & Georges M. Fadel & Alexander Engau & Brian J. Hunt & Vijay Singh, 2009. "Multi-scenario Multi-objective Optimization with Applications in Engineering Design," Lecture Notes in Economics and Mathematical Systems, in: Vincent Barichard & Matthias Ehrgott & Xavier Gandibleux & Vincent T'Kindt (ed.), Multiobjective Programming and Goal Programming, pages 283-298, Springer.
    4. Ulrich Junker, 2004. "Preference-Based Search and Multi-Criteria Optimization," Annals of Operations Research, Springer, vol. 130(1), pages 75-115, August.
    5. JosÉ Figueira & Salvatore Greco & Matthias Ehrogott, 2005. "Multiple Criteria Decision Analysis: State of the Art Surveys," International Series in Operations Research and Management Science, Springer, number 978-0-387-23081-8, April.
    6. Weber,Elke U. & Baron,Jonathan & Loomes,Graham (ed.), 2001. "Conflict and Tradeoffs in Decision Making," Cambridge Books, Cambridge University Press, number 9780521772389, October.
    7. I. Kaliszewski & W. Michalowski, 1997. "Efficient Solutions and Bounds on Tradeoffs," Journal of Optimization Theory and Applications, Springer, vol. 94(2), pages 381-394, August.
    8. Podinovskii, Vladislav V., 1994. "Criteria importance theory," Mathematical Social Sciences, Elsevier, vol. 27(3), pages 237-252, June.
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    Cited by:

    1. Daniel Vanderpooten & Lakmali Weerasena & Margaret M. Wiecek, 2017. "Covers and approximations in multiobjective optimization," Journal of Global Optimization, Springer, vol. 67(3), pages 601-619, March.
    2. 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.
    3. Stephan Dempe & Gabriele Eichfelder & Jörg Fliege, 2015. "On the effects of combining objectives in multi-objective optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 82(1), pages 1-18, August.
    4. Kaddani, Sami & Vanderpooten, Daniel & Vanpeperstraete, Jean-Michel & Aissi, Hassene, 2017. "Weighted sum model with partial preference information: Application to multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 260(2), pages 665-679.
    5. Mut, Murat & Wiecek, Margaret M., 2011. "Generalized equitable preference in multiobjective programming," European Journal of Operational Research, Elsevier, vol. 212(3), pages 535-551, August.
    6. Jiménez, Mariano & Bilbao-Terol, Amelia & Arenas-Parra, Mar, 2021. "Incorporating preferential weights as a benchmark into a Sequential Reference Point Method," European Journal of Operational Research, Elsevier, vol. 291(2), pages 575-585.
    7. Arne Herzel & Stephan Helfrich & Stefan Ruzika & Clemens Thielen, 2023. "Approximating biobjective minimization problems using general ordering cones," Journal of Global Optimization, Springer, vol. 86(2), pages 393-415, June.

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