Decomposition based dominance relationship for evolutionary many-objective algorithm

Lei Chen, Hai Lin Liu, Kay Chen Tan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Decomposition based evolutionary algorithms have achieved great success in solving many-objective optimization problems. However, the design of proper decomposition vectors is not an easy task, especially in high dimensional objective space. In this paper, we study how to better use these decomposition vectors. We first show that for any given decomposition vector, new dominance relationship and crowding measurement strategy can be well defined. Based on them, we then propose a new evolutionary algorithm for many objective optimization. By this way, the utilization efficiency of decomposition vectors is enhanced and thus the task of weights design is alleviated accordingly. Experiments are conducted to compare the proposed algorithm with four state-of-the-art decomposition based evolutionary algorithms on a set of well-known many-objective test problems with 5 to 10 objectives. The simulation results show that the proposed algorithm can achieve comparable results with fewer decomposition vectors.

Original languageEnglish
Title of host publication2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538627259
DOIs
Publication statusPublished - 2 Feb 2018
Externally publishedYes
Event2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Honolulu, United States
Duration: 27 Nov 20171 Dec 2017

Publication series

Name2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
Volume2018-January

Conference

Conference2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017
Country/TerritoryUnited States
CityHonolulu
Period27/11/171/12/17

Keywords

  • decomposition
  • dominance relationship
  • evolutionary algorithm
  • Many-objective

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Optimization

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