1998•Or TransactionsRequires access

Duality Theorems of Multiobjective Programming for a Class of Generalized Convex Functions

Yingying Wang, D Jiali

Open publisher page 0 citations

Abstract

In this paper, a class of more general generalized convex functions: (F, p)-invariantconvexity functions, are defined. On the basis of defintions, we have constructed generalduality models (VD); discussed duality property of (VP) and (VD); proved weakly dualitytheorem, direct duality theorem and converse duality theorem.

About this research paper

What this paper is about

In this paper, a class of more general generalized convex functions: (F, p)-invariantconvexity functions, are defined. On the basis of defintions, we have constructed generalduality models (VD); discussed duality property of (VP) and (VD); proved weakly dualitytheorem, direct duality theorem and converse duality theorem.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In this paper, a class of more general generalized convex functions: (F, p)-invariantconvexity functions, are defined. On the basis of defintions, we have constructed generalduality models (VD); discussed duality property of (VP) and (VD); proved weakly dualitytheorem, direct duality theorem and converse duality theorem.

Key concepts: Fenchel's duality theorem, Duality (order theory), Perturbation function, Mathematics, Converse, Strong duality, Weak duality, Convex analysis

Related papers

Back to paper searchBrowse research topicsOriginal source
Duality Theorems of Multiobjective Programming for a Class of Generalized Convex Functions — Research Paper | ScholarLens