A Comprehensive Review on Evolutionary Algorithm Solving Multi-Objective Problems

Ying Qu*, Zheng Ma, Anders Clausen, Bo Nørregaard Jørgensen

*Kontaktforfatter for dette arbejde

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstrakt

In the real world, it is challenging to determine optimal solutions over multiple conflicting objectives in complex systems. As a mainstream method for solving multi-objective problems, the development and the application of Evolutionary Algorithm (EA) methods have attracted thousands of researches since the 1950s. However, as we know, there are few studies on the comprehensive review of multi-objective EA (MOEA) methods in general domains. In this review research, firstly, the categories of MOEA methods according to the classification strategy of reproduction operators is proposed. Then, a systematic literature search methodology and logical citation management are introduced in order to create a literature pool for further analysis. On the basis of the literature pool, the categories of MOEA methods concerning three aspects and the application domains are analyzed. The purpose of this review is to provide a comprehensive view and a guide reference for the MOEA method selection on solving a specific type of multi-objective optimization problems (MOPs).
OriginalsprogEngelsk
Titel2021 22nd IEEE International Conference on Industrial Technology (ICIT)
ForlagIEEE
Publikationsdato2021
Sider825-831
ISBN (Elektronisk)978-1-7281-5730-6
DOI
StatusUdgivet - 2021
Begivenhed22nd IEEE International Conference on Industrial Technology - Valencia Conference Centre, Valencia, Spanien
Varighed: 10. mar. 202112. mar. 2021
Konferencens nummer: 22
https://ieee-icit2021.org/

Konference

Konference22nd IEEE International Conference on Industrial Technology
Nummer22
LokationValencia Conference Centre
Land/OmrådeSpanien
ByValencia
Periode10/03/202112/03/2021
Internetadresse

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