Dynamic multi-objective differential evolution for solving constrained optimization problem

Lina Jia, Sanyou Zeng, Dong Zhou, Aimin Zhou, Zhengjun Li, Hongyong Jing

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Dynamic constrained multi-objective differential evolution(DCMODE) is designed for solving constrained optimization problem(COP). Main feature presented in this paper is to construct dynamic multi-objective optimization problem(DMOP) from COP. The two evolved objectives are original function objective and violation objective. Constraints are controlled by dynamic environments, where the relaxed constraints boundaries are gradually tightened to original boundaries. After this dynamic process, DMOP solutions are close to COP solution. This new algorithm is tested on benchmark problems of special session at CEC2006 with 100% success rates of all problems. Compared with several state-of-the-art DE variants referred in this paper, our algorithm outperforms or performs similarly to them. The satisfactory results suggest that it is efficient and generic when handling inequality/equality constraints.

Original languageEnglish
Title of host publication2011 IEEE Congress of Evolutionary Computation, CEC 2011
Pages2649-2654
Number of pages6
DOIs
StatePublished - 2011
Event2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA, United States
Duration: 5 Jun 20118 Jun 2011

Publication series

Name2011 IEEE Congress of Evolutionary Computation, CEC 2011

Conference

Conference2011 IEEE Congress of Evolutionary Computation, CEC 2011
Country/TerritoryUnited States
CityNew Orleans, LA
Period5/06/118/06/11

Keywords

  • Constrained optimization
  • Differential Evolution
  • Dynamic Constrained Multi-objective Optimization

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