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Optimality conditions for invex nonsmooth optimization problems with fuzzy objective functions

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  • Tadeusz Antczak

    (University of Łódź)

Abstract

In this paper, the definitions of Clarke generalized directional $$\alpha $$ α -derivative and Clarke generalized gradient are introduced for a locally Lipschitz fuzzy function. Further, a nonconvex nonsmooth optimization problem with fuzzy objective function and both inequality and equality constraints is considered. The Karush-Kuhn-Tucker optimality conditions are established for such a nonsmooth extremum problem. For proving these conditions, the approach is used in which, for the considered nonsmooth fuzzy optimization problem, its associated bi-objective optimization problem is constructed. The bi-objective optimization problem is solved by its associated scalarized problem constructed in the weighting method. Then, under invexity hypotheses, (weakly) nondominated solutions in the considered nonsmooth fuzzy minimization problem are characterized through Pareto solutions in its associated bi-objective optimization problem and Karush-Kuhn-Tucker points of the weighting problem.

Suggested Citation

  • Tadeusz Antczak, 2023. "Optimality conditions for invex nonsmooth optimization problems with fuzzy objective functions," Fuzzy Optimization and Decision Making, Springer, vol. 22(1), pages 1-21, March.
    • Handle: RePEc:spr:fuzodm:v:22:y:2023:i:1:d:10.1007_s10700-022-09381-4
    DOI: 10.1007/s10700-022-09381-4
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    References listed on IDEAS

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    1. Panigrahi, Motilal & Panda, Geetanjali & Nanda, Sudarsan, 2008. "Convex fuzzy mapping with differentiability and its application in fuzzy optimization," European Journal of Operational Research, Elsevier, vol. 185(1), pages 47-62, February.
    2. Hsien-Chung Wu, 2007. "The Karush-Kuhn-Tucker optimality conditions for the optimization problem with fuzzy-valued objective function," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 66(2), pages 203-224, October.
    3. Wu, Hsien-Chung, 2009. "The Karush-Kuhn-Tucker optimality conditions in multiobjective programming problems with interval-valued objective functions," European Journal of Operational Research, Elsevier, vol. 196(1), pages 49-60, July.
    4. Wu, Hsien-Chung, 2007. "The Karush-Kuhn-Tucker optimality conditions in an optimization problem with interval-valued objective function," European Journal of Operational Research, Elsevier, vol. 176(1), pages 46-59, January.
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