Solving multimodal optimization problems through a multiobjective optimization approach

Jing-Yu JI, Wei-Jie YU*, Wei-Neng CHEN, Zhi-Hui ZHAN, Jun ZHANG

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

This paper proposes a novel multi-objective optimization approach for solving multimodal optimization problems (MMOPs). An MMOP at hand is first transformed into a bi-objective optimization problem. The two objectives are constructed totally conflict by using the distance information and the objective function value. In this way, multiple optima of an MMOP are converted into the non-dominated solutions of the transformed bi-objective optimization problem. Then, multi-objective optimization techniques based on differential evolution are applied to solve the bi-objective problem. In addition, a modified solution comparison criterion is proposed to improve the accuracy level of the final solutions. The performance of the proposed approach is evaluated on a suite of benchmark functions. Experimental results show that the proposed approach is very competitive compared with six state-of-The-Art multimodal optimization algorithms on most of the benchmark functions.

Original languageEnglish
Title of host publication7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages458-463
Number of pages6
ISBN (Electronic)9781509054015
DOIs
Publication statusPublished - 11 May 2017
Externally publishedYes
Event7th International Conference on Information Science and Technology, ICIST 2017 - Da Nang, Viet Nam
Duration: 16 Apr 201719 Apr 2017

Publication series

Name7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings

Conference

Conference7th International Conference on Information Science and Technology, ICIST 2017
Country/TerritoryViet Nam
CityDa Nang
Period16/04/1719/04/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

  • differential evolution
  • multimodal optimization problems
  • multiobjective optimization

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