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Reseach Article

Multiobjective Optimization of Electrical Machine, a State of the Art Study

by P. Ponmurugan, N. Rengarajan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 56 - Number 13
Year of Publication: 2012
Authors: P. Ponmurugan, N. Rengarajan
10.5120/8953-3136

P. Ponmurugan, N. Rengarajan . Multiobjective Optimization of Electrical Machine, a State of the Art Study. International Journal of Computer Applications. 56, 13 ( October 2012), 26-30. DOI=10.5120/8953-3136

@article{ 10.5120/8953-3136,
author = { P. Ponmurugan, N. Rengarajan },
title = { Multiobjective Optimization of Electrical Machine, a State of the Art Study },
journal = { International Journal of Computer Applications },
issue_date = { October 2012 },
volume = { 56 },
number = { 13 },
month = { October },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume56/number13/8953-3136/ },
doi = { 10.5120/8953-3136 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:58:44.932603+05:30
%A P. Ponmurugan
%A N. Rengarajan
%T Multiobjective Optimization of Electrical Machine, a State of the Art Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 56
%N 13
%P 26-30
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a literal study of Multiobjective optimization (MO) in general used in electrical machine optimization in the recent years. A set of a set of nonlinear constraints (modeling availability of resources) with a set of nonlinear objective functions (modeling several performance criteria) is solved with the help of Multi objective optimization (MO). The MO problem has several applications in science, engineering, finance, etc. It is normally not possible to find an optimal solution in MO, since the various objective functions in the problem are usually in conflict with each other. Therefore, the objective in MO is to find the Pareto front of efficient solutions that provide a substitution between the various objectives. The paper will summon up some of the work done using Multiobjective optimization on electric machines in the last years. An overview of methods used will be given and the conclusion of the different papers will be presented.

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Index Terms

Computer Science
Information Sciences

Keywords

Multiobjective Optimization Pareto front Evolutionary algorithms induction machine