An evolutionary algorithm based on decomposition for multimodal optimization problems

Fangqing Gu, Yiu Ming CHEUNG, Jie Luo

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

This paper presents a non-parameter method to identify the peaks of the multi-modal optimization problems provided that the peaks are characterized by a smaller objective values than their neighbors and by a relatively large distance from points with smaller objective value. Using the identified peaks as the seeds, we decompose the population into some subpopulations and dynamically allocate the computational effort to different subpopulations. We evaluate the proposed approach on the CEC2015 single objective multi-niche optimization problems. The promising experimental results show its efficacy.

Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1091-1097
Number of pages7
ISBN (Electronic)9781479974924
DOIs
Publication statusPublished - 10 Sep 2015
EventIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan
Duration: 25 May 201528 May 2015

Publication series

Name2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

Conference

ConferenceIEEE Congress on Evolutionary Computation, CEC 2015
Country/TerritoryJapan
CitySendai
Period25/05/1528/05/15

Scopus Subject Areas

  • Computer Science Applications
  • Computational Mathematics

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