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2009•Unpublished venueRequires access

CONJUGATE DUALITY FOR SET-VALUED VECTOR OPTIMIZATION IN FINITE DIMENSIONAL SPACES

Shui-Jing Yun, Guoyong Liu, Li-Ping Pang

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Abstract

In this paper, we consider conjugate duality theorem in set-valued vector optimization. New perturbation function is presented for a class of set- valued vector optimization, in order to obtain corresponding conjugate duality optimization and duality theorems. We show under a stability criteria that the form of weak and strong duality becomes simple, general and convenient in

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What this paper is about

In this paper, we consider conjugate duality theorem in set-valued vector optimization. New perturbation function is presented for a class of set- valued vector optimization, in order to obtain corresponding conjugate duality optimization and duality theorems. We show under a stability criteria that the form of weak and strong duality becomes simple, general and convenient in

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Available abstract

In this paper, we consider conjugate duality theorem in set-valued vector optimization. New perturbation function is presented for a class of set- valued vector optimization, in order to obtain corresponding conjugate duality optimization and duality theorems. We show under a stability criteria that the form of weak and strong duality becomes simple, general and convenient in

Key concepts: Perturbation function, Duality (order theory), Strong duality, Mathematics, Fenchel's duality theorem, Duality gap, Vector optimization, Weak duality

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