Optimality Conditions for Multiobjective Optimization Problems via Image Space Analysis

In this article, optimality conditions on (weak) efficient solutions in multiobjective optimization problems are investigated by using the image space analysis. A class of strong separation functions is constructed by oriented distance functions. Simultaneously, a generalized Lagrange function is in...

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Bibliographic Details
Published in:	Numerical functional analysis and optimization Vol. 44; no. 7; pp. 708 - 723
Main Authors:	Xu, Yingrang, Li, Shengjie
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 19.05.2023 Taylor & Francis Ltd
Subjects:	90C29 90C46 Generalized KKT necessary conditions image space analysis Lagrangian-type sufficient conditions Multiple objective analysis Optimization Separation strong separation function
ISSN:	0163-0563, 1532-2467
Online Access:	Get full text
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Summary:	In this article, optimality conditions on (weak) efficient solutions in multiobjective optimization problems are investigated by using the image space analysis. A class of strong separation functions is constructed by oriented distance functions. Simultaneously, a generalized Lagrange function is introduced by the class of strong separation functions. Then, generalized Karush-Kuhn-Tucker (KKT for short) necessary optimality conditions are established without constraint qualifications or regularity conditions. Under the suitable assumptions, Lagrangian-type sufficient optimality conditions are also characterized. Moreover, the difference between strong separation and weak separation methods is explained.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0163-0563 1532-2467
DOI:	10.1080/01630563.2023.2208867