A decomposition based multiobjective evolutionary algorithm with classification

Xi LIN, Qingfu ZHANG, Sam KWONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

28 Citations (Scopus)

Abstract

This paper investigates how to use a pre-selection approach to improve the performance of the multiobjective evolutionary algorithm based on decomposition (MOEA/D). It proposes a novel MOEA/D algorithm with classification to serve this purpose. The proposed algorithm builds a classification model on the search space to filter all new generated solutions, and mainly evaluates those promising solutions for reducing real function evaluation costs during the search process. Experimental study on different test instances validates that the pre-selection approach can significantly improve the performance of a classical MOEA/D.
Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherIEEE
Pages3292-3299
Number of pages8
ISBN (Electronic)9781509006236
ISBN (Print)9781509006243
DOIs
Publication statusPublished - 14 Nov 2016
Externally publishedYes
Event2016 IEEE Congress on Evolutionary Computation - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Conference

Conference2016 IEEE Congress on Evolutionary Computation
Abbreviated titleCEC 2016
Country/TerritoryCanada
CityVancouver
Period24/07/1629/07/16

Bibliographical note

This work was supported by the National Natural Science Foundation of China under Grants 61473241.

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