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2001•Numerical Functional Analysis and OptimizationRequires access

SUFFICIENT OPTIMALITY CONDITIONS AND DUALITY IN MULTIOBJECTIVE OPTIMIZATION INVOLVING GENERALIZED CONVEXITY

Brahim Aghezzaf, Mohamed Hachimi

Open publisher page 11 citations

Abstract

We are concerned with nonlinear multiobjective programming problem with inequality constraints. We introduce some classes of nonconvex functions by relaxing the definitions of invex and preinvex functions. Examples are given to shows relationship between them. Various first and second order sufficient optimality theorems are obtained. Moreover, we prove duality and converse duality results for Mond-Weir type dual.

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What this paper is about

We are concerned with nonlinear multiobjective programming problem with inequality constraints. We introduce some classes of nonconvex functions by relaxing the definitions of invex and preinvex functions. Examples are given to shows relationship between them. Various first and second order sufficient optimality theorems are obtained. Moreover, we prove duality and converse duality results for Mond-Weir type dual.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

We are concerned with nonlinear multiobjective programming problem with inequality constraints. We introduce some classes of nonconvex functions by relaxing the definitions of invex and preinvex functions. Examples are given to shows relationship between them. Various first and second order sufficient optimality theorems are obtained. Moreover, we prove duality and converse duality results for Mond-Weir type dual.

Key concepts: Duality (order theory), Mathematics, Converse, Convexity, Wolfe duality, Multiobjective programming, Strong duality, Duality gap

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