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Journal of Heuristics

, Volume 1, Issue 2, pp 177–206 | Cite as

Heuristic methods for evolutionary computation techniques

  • Zbigniew Michalewicz
Article

Abstract

Evolutionary computation techniques, which are based on a powerful principle of evolution—survival of the fittest, constitute an interesting category of heuristic search. In other words, evolutionary techniques are stochastic algorithms whose search methods model some natural phenomena: genetic inheritance and Darwinian strife for survival.

Any evolutionary algorithm applied to a particular problem must address the issue of genetic representation of solutions to the problem and genetic operators that would alter the genetic composition of offspring during the reproduction process. However, additional heuristics should be incorporated in the algorithm as well; some of these heuristic rules provide guidelines for evaluating (feasible and infeasible) individuals in the population. This paper surveys such heuristics and discusses their merits and drawbacks.

Key Words

constrained optimization evolutionary computation genetic algorithms infeasible individuals 

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Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Zbigniew Michalewicz
    • 1
    • 2
  1. 1.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA
  2. 2.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

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