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Scalarizing cost‐effective multi‐objective optimization algorithms made possible with kriging

Scalarizing cost‐effective multi‐objective optimization algorithms made possible with kriging Purpose – The purpose of this paper is threefold: to make explicitly clear the range of efficient multi‐objective optimization algorithms which are available with kriging; to demonstrate a previously uninvestigated algorithm on an electromagnetic design problem; and to identify algorithms particularly worthy of investigation in this field. Design/methodology/approach – The paper concentrates exclusively on scalarizing multi‐objective optimization algorithms. By reviewing the range of selection criteria based on kriging models for single‐objective optimization along with the range of methods available for transforming a multi‐objective optimization problem to a single‐objective problem, the family of scalarizing multi‐objective optimization algorithms is made explicitly clear. Findings – One of the proposed algorithms is demonstrated on the multi‐objective design of an electron gun. It is able to identify efficiently an approximation to the Pareto‐optimal front. Research limitations/implications – The algorithms proposed are applicable to unconstrained problems only. One future development is to incorporate constraint‐handling techniques from single‐objective optimization into the scalarizing algorithms. Originality/value – A family of algorithms, most of which have not been explored before in the literature, is proposed. Algorithms of particular potential (utilizing the most promising developments in single‐objective optimization) are identified. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering Emerald Publishing

Scalarizing cost‐effective multi‐objective optimization algorithms made possible with kriging

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Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
0332-1649
DOI
10.1108/03321640810878243
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is threefold: to make explicitly clear the range of efficient multi‐objective optimization algorithms which are available with kriging; to demonstrate a previously uninvestigated algorithm on an electromagnetic design problem; and to identify algorithms particularly worthy of investigation in this field. Design/methodology/approach – The paper concentrates exclusively on scalarizing multi‐objective optimization algorithms. By reviewing the range of selection criteria based on kriging models for single‐objective optimization along with the range of methods available for transforming a multi‐objective optimization problem to a single‐objective problem, the family of scalarizing multi‐objective optimization algorithms is made explicitly clear. Findings – One of the proposed algorithms is demonstrated on the multi‐objective design of an electron gun. It is able to identify efficiently an approximation to the Pareto‐optimal front. Research limitations/implications – The algorithms proposed are applicable to unconstrained problems only. One future development is to incorporate constraint‐handling techniques from single‐objective optimization into the scalarizing algorithms. Originality/value – A family of algorithms, most of which have not been explored before in the literature, is proposed. Algorithms of particular potential (utilizing the most promising developments in single‐objective optimization) are identified.

Journal

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic EngineeringEmerald Publishing

Published: Jul 11, 2008

Keywords: Optimization techniques; Programming and algorithm theory

References