Evolutionary multimodal optimization using the principle of locality

Kachun Wong, Chunho Wu, Ricky Mok, Chengbin Peng, Zhaolei Zhang

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.
Original languageEnglish (US)
Pages (from-to)138-170
Number of pages33
JournalInformation Sciences
Volume194
DOIs
StatePublished - Jul 2012

ASJC Scopus subject areas

  • Artificial Intelligence
  • Theoretical Computer Science
  • Software
  • Information Systems and Management
  • Control and Systems Engineering
  • Computer Science Applications

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