Optimality conditions for invex nonsmooth optimization problems with fuzzy objective functions

In this paper, the definitions of Clarke generalized directional 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 cons...

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Veröffentlicht in:Fuzzy optimization and decision making Jg. 22; H. 1; S. 1 - 21
1. Verfasser: Antczak, Tadeusz
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.03.2023
Springer Nature B.V
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ISSN:1568-4539, 1573-2908
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Zusammenfassung:In this paper, the definitions of Clarke generalized directional 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.
Bibliographie:ObjectType-Article-1
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ISSN:1568-4539
1573-2908
DOI:10.1007/s10700-022-09381-4