Cooperatively coevolving particle swarms for large scale optimization

Xiaodong LI, Xin YAO

Research output: Journal PublicationsJournal Article (refereed)peer-review

673 Citations (Scopus)

Abstract

This paper presents a new cooperative coevolving particle swarm optimization (CCPSO) algorithm in an attempt to address the issue of scaling up particle swarm optimization (PSO) algorithms in solving large-scale optimization problems (up to 2000 real-valued variables). The proposed CCPSO2 builds on the success of an early CCPSO that employs an effective variable grouping technique random grouping. CCPSO2 adopts a new PSO position update rule that relies on Cauchy and Gaussian distributions to sample new points in the search space, and a scheme to dynamically determine the coevolving subcomponent sizes of the variables. On high-dimensional problems (ranging from 100 to 2000 variables), the performance of CCPSO2 compared favorably against a state-of-the-art evolutionary algorithm sep-CMA-ES, two existing PSO algorithms, and a cooperative coevolving differential evolution algorithm. In particular, CCPSO2 performed significantly better than sep-CMA-ES and two existing PSO algorithms on more complex multimodal problems (which more closely resemble real-world problems), though not as well as the existing algorithms on unimodal functions. Our experimental results and analysis suggest that CCPSO2 is a highly competitive optimization algorithm for solving large-scale and complex multimodal optimization problems. © 2011 IEEE.
Original languageEnglish
Article number5910380
Pages (from-to)210-224
Number of pages15
JournalIEEE Transactions on Evolutionary Computation
Volume16
Issue number2
Early online date28 Jun 2011
DOIs
Publication statusPublished - Apr 2012
Externally publishedYes

Bibliographical note

This work was supported by EPSRC, under Grant EP/G002339/1, which funded the first author’s two trips to Birmingham, U.K., as a Visiting Research Fellow in 2008 and 2009.

Keywords

  • Cooperative coevolution
  • evolutionary algorithms
  • large-scale optimization
  • particle swarm optimization
  • swarm intelligence

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