2010Journal of Numerical Analysis and Approximation TheoryOpen access

Vector optimization problems and approximated vector optimization problems

Eugenia Duca, Dorel I. Duca

Open full text 0 citations

Abstract

In this paper, a so-called approximated vector optimization problem associated to a vector optimization problem is considered. The equivalence between the efficient solutions of the approximated vector optimization problem and efficient solutions of the original optimization problem is established.

Open-access reader

About this research paper

What this paper is about

In this paper, a so-called approximated vector optimization problem associated to a vector optimization problem is considered. The equivalence between the efficient solutions of the approximated vector optimization problem and efficient solutions of the original optimization problem is established.

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 so-called approximated vector optimization problem associated to a vector optimization problem is considered. The equivalence between the efficient solutions of the approximated vector optimization problem and efficient solutions of the original optimization problem is established.

Key concepts: Vector optimization, Optimization problem, Mathematical optimization, Mathematics, Equivalence (formal languages), Vector (molecular biology), Continuous optimization, Multi-swarm optimization

Related papers

Back to paper searchBrowse research topicsOriginal source
Vector optimization problems and approximated vector optimization problems — Research Paper | ScholarLens