Displaying similar documents to “Generalized ( , b , φ , ρ , θ ) -univex n -set functions and global semiparametric sufficient efficiency conditions in multiobjective fractional subset programming.”

Optimality conditions for weak efficiency to vector optimization problems with composed convex functions

Radu Boţ, Ioan Hodrea, Gert Wanka (2008)

Open Mathematics

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We consider a convex optimization problem with a vector valued function as objective function and convex cone inequality constraints. We suppose that each entry of the objective function is the composition of some convex functions. Our aim is to provide necessary and sufficient conditions for the weakly efficient solutions of this vector problem. Moreover, a multiobjective dual treatment is given and weak and strong duality assertions are proved.

Weighted scalarization related to L p -metric and pareto optimality

Alexandra Šipošová (2008)

Kybernetika

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Relations between (proper) Pareto optimality of solutions of multicriteria optimization problems and solutions of the minimization problems obtained by replacing the multiple criteria with L p -norm related functions (depending on the criteria, goals, and scaling factors) are investigated.

Comparison between different duals in multiobjective fractional programming

Radu Boţ, Robert Chares, Gert Wanka (2007)

Open Mathematics

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The present paper is a continuation of [2] where we deal with the duality for a multiobjective fractional optimization problem. The basic idea in [2] consists in attaching an intermediate multiobjective convex optimization problem to the primal fractional problem, using an approach due to Dinkelbach ([6]), for which we construct then a dual problem expressed in terms of the conjugates of the functions involved. The weak, strong and converse duality statements for the intermediate problems...

Nonsmooth equations approach to a constrained minimax problem

Yan Gao, Xuewen Li (2005)

Applications of Mathematics

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An equivalent model of nonsmooth equations for a constrained minimax problem is derived by using a KKT optimality condition. The Newton method is applied to solving this system of nonsmooth equations. To perform the Newton method, the computation of an element of the b -differential for the corresponding function is developed.