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Genetic Algorithms

In: Handbook of Metaheuristics

Author

Listed:
  • Colin R. Reeves

    (Coventry University)

Abstract

Genetic algorithms (GAs) have become popular as a means of solving hard combinatorial optimization problems. The first part of this chapter briefly traces their history, explains the basic concepts and discusses some of their theoretical aspects. It also references a number of sources for further research into their applications. The second part concentrates on the detailed implementation of a GA. It discusses the fundamentals of encoding a ‘genotype’ in different circumstances and describes the mechanics of population selection and management and the choice of genetic ‘operators’ for generating new populations. In closing, some specific guidelines for using GAs in practice are provided.

Suggested Citation

  • Colin R. Reeves, 2010. "Genetic Algorithms," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 109-139, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-1665-5_5
    DOI: 10.1007/978-1-4419-1665-5_5
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