Recent advances in evolutionary computation

Xin YAO, Yong XU

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

102 Citations (Scopus)

Abstract

Evolutionary computation has experienced a tremendous growth in the last decade in both theoretical analyses and industrial applications. Its scope has evolved beyond its original meaning of "biological evolution" toward a wide variety of nature inspired computational algorithms and techniques, including evolutionary, neural, ecological, social and economical computation, etc., in a unified framework. Many research topics in evolutionary computation nowadays are not necessarily "evolutionary". This paper provides an overview of some recent advances in evolutionary computation that have been made in CERCIA at the University of Birmingham, UK. It covers a wide range of topics in optimization, learning and design using evolutionary approaches and techniques, and theoretical results in the computational time complexity of evolutionary algorithms. Some issues related to future development of evolutionary computation are also discussed.
Original languageEnglish
Pages (from-to)1-18
Number of pages18
JournalJournal of Computer Science and Technology
Volume21
Issue number1
DOIs
Publication statusPublished - Jan 2006
Externally publishedYes

Keywords

  • Computational time complexity
  • Evolutionary computation
  • Neural network ensemble
  • Prisoner's dilemma
  • Real-world application

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