A method of genetic algorithm based multiobjective optimization via cooperative coevolution

Jongsoo Lee, Doyoung Kim

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

Original languageEnglish
Pages (from-to)2115-2123
Number of pages9
JournalJournal of Mechanical Science and Technology
Issue number12
Publication statusPublished - 2006 Dec

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering


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