Adaptive Chemical Reaction Optimization for global numerical optimization

James J.Q. Yu, Yun Sang Albert LAM, Victor O.K. Li

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

9 Citations (Scopus)

Abstract

A newly proposed chemical-reaction-inspired metaheurisic, Chemical Reaction Optimization (CRO), has been applied to many optimization problems in both discrete and continuous domains. To alleviate the effort in tuning parameters, this paper reduces the number of optimization parameters in canonical CRO and develops an adaptive scheme to evolve them. Our proposed Adaptive CRO (ACRO) adapts better to different optimization problems. We perform simulations with ACRO on a widely-used benchmark of continuous problems. The simulation results show that ACRO has superior performance over canonical CRO.

Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3192-3199
Number of pages8
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

User-Defined Keywords

  • adaptive scheme
  • Chemical Reaction Optimization
  • continuous optimization
  • evolutionary algorithm
  • metaheuristic

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