Displaying similar documents to “Optimality conditions for a class of mathematical programs with equilibrium constraints: strongly regular case”

Sufficient Second Order Optimality Conditions for C^1 Multiobjective Optimization Problems

Gadhi, N. (2003)

Serdica Mathematical Journal

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2000 Mathematics Subject Classification: Primary 90C29; Secondary 90C30. In this work, we use the notion of Approximate Hessian introduced by Jeyakumar and Luc [19], and a special scalarization to establish sufficient optimality conditions for constrained multiobjective optimization problems. Throughout this paper, the data are assumed to be of class C^1, but not necessarily of class C^(1.1).

On necessary optimality conditions in a class of optimization problems

Jiří V. Outrata (1989)

Aplikace matematiky

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In the paper necessary optimality conditions are derived for the minimization of a locally Lipschitz objective with respect to the consttraints x ∈ S , 0 ∈ F ( x ) , where S is a closed set and F is a set-valued map. No convexity requirements are imposed on F . The conditions are applied to a generalized mathematical programming problem and to an abstract finite-dimensional optimal control problem.

Second-order optimality conditions for nondominated solutions of multiobjective programming with C 1 , 1 data

Liping Liu, Pekka Neittaanmäki, Michal Křížek (2000)

Applications of Mathematics

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We examine new second-order necessary conditions and sufficient conditions which characterize nondominated solutions of a generalized constrained multiobjective programming problem. The vector-valued criterion function as well as constraint functions are supposed to be from the class C 1 , 1 . Second-order optimality conditions for local Pareto solutions are derived as a special case.

LFS functions in multi-objective programming

Luka Neralić, Sanjo Zlobec (1996)

Applications of Mathematics

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We find conditions, in multi-objective convex programming with nonsmooth functions, when the sets of efficient (Pareto) and properly efficient solutions coincide. This occurs, in particular, when all functions have locally flat surfaces (LFS). In the absence of the LFS property the two sets are generally different and the characterizations of efficient solutions assume an asymptotic form for problems with three or more variables. The results are applied to a problem in highway construction,...