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Evolution Strategies and Evolutionary Programming

  • Anthony Brabazon
  • Michael O’Neill
  • Seán McGarraghy
Part of the Natural Computing Series book series (NCS)

Abstract

In this chapter, two significant evolutionary algorithms, evolution strategies and evolutionary programming, are presented.

Evolution strategies (ES) was developed by Rechenberg and Schwefel [530, 531, 560, 561] in the 1960s and attracted a large following amongst researchers and practitioners, particularly in Europe. ES has been extensively used as a tool for solving real-valued optimisation problems and has also been successfully applied for combinatorial optimisation, for constrained optimisation and for multiobjective optimisation.

Keywords

Evolution Strategy Travel Salesman Problem Strategy Parameter Solution Vector Success Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Anthony Brabazon
    • 1
  • Michael O’Neill
    • 1
  • Seán McGarraghy
    • 1
  1. 1.Natural Computing Research & Applications Group School of BusinessUniversity College DublinDublinIreland

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