Dynamic Cooperative Coevolution for Large Scale Optimization

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

1 Scopus Citations
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Author(s)

  • Xin-Yuan Zhang
  • Yue Jiao Gong
  • Ying Lin
  • Jie Zhang
  • Jun Zhang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)935-948
Journal / PublicationIEEE Transactions on Evolutionary Computation
Volume23
Issue number6
Online published28 Jan 2019
Publication statusPublished - Dec 2019

Abstract

The cooperative coevolution (CC) framework achieves a promising performance in solving large scale global optimization problems. The framework encounters difficulties on nonseparable problems, where variables interact with each other. Using the static grouping methods, variables will be theoretically grouped into one big subcomponent, whereas the random grouping strategy endures low efficiency. In this paper, a dynamic CC framework is proposed to tackle the challenge. The proposed framework works in a computationally efficient manner, in which the computational resources are allocated to a series of elitist subcomponents consisting of superior variables. First, a novel estimation method is proposed to evaluate the contribution of variables using the historical information of the best overall fitness. Based on the contribution and the interaction information, a dynamic grouping strategy is conducted to construct the dynamic subcomponent that evolves in the next evolutionary period. The constructed subcomponents are different from each other, and therefore the required parameters to control the optimization of each subcomponent vary a lot in each evolutionary period. A stage-by-stage parameter adaptation strategy is proposed to adapt the optimizer to the dynamic optimization environment. Experimental results indicate that the proposed framework achieves competitive results compared with the state-of-the-art CC frameworks.

Research Area(s)

  • Cooperative coevolution, dynamic grouping strategy., large scale global optimization, non-separable problems

Citation Format(s)

Dynamic Cooperative Coevolution for Large Scale Optimization. / Zhang, Xin-Yuan; Gong, Yue Jiao; Lin, Ying; Zhang, Jie; Kwong, Sam; Zhang, Jun.

In: IEEE Transactions on Evolutionary Computation, Vol. 23, No. 6, 12.2019, p. 935-948.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal