Smart use of computational resources based on contribution for cooperative co-evolutionary algorithms

Mohammad N. OMIDVAR, Xiaodong LI, Xin YAO

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

110 Citations (Scopus)

Abstract

Standard Cooperative Co-evolution uses a round-robin method to select subcomponents to undergo optimization. In a non-separable (epistatic) optimization problem, dividing the computational budget equally between all of the subcomponents is not necessarily the best strategy. When dealing with non-separable problems, there is usually an imbalance between the contribution of various subcomponents to the global fitness of the individuals. Using a round-robin fashion treats all of the subcomponents equally and wastes the computational budget. In this paper, we propose a Contribution Based Cooperative Co-evolution (CBCC) that selects the subcomponents based on their contributions to the global fitness. This alleviates the imbalance issue and allows the computational resources to be used more efficiently. Experiments on several benchmark functions with the "imbalance issue" show that this new scheme is promising, especially when it is combined with a grouping algorithm that captures interacting variables in common subcomponents. Copyright 2011 ACM.
Original languageEnglish
Title of host publicationGenetic and Evolutionary Computation Conference, GECCO'11
Pages1115-1122
Number of pages8
DOIs
Publication statusPublished - 12 Jul 2011
Externally publishedYes

Keywords

  • Contribution based cooperative co-evolution
  • Evolutionary algorithms
  • Large scale optimization
  • Non-separability

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