The effect of genetic operator probabilities and selection strategies on the performance of a genetic algorithm

  • Kay Wiese
  • Scott D. Goodwin
Genetic Algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1418)


This paper presents a comparison of two genetic algorithms (GAs) that use different selection strategies. The first GA uses the standard selection strategy of roulette wheel selection and generational replacement (STDS), while the second GA uses an intermediate selection strategy in addition to STDS. Our previous research has shown that this intermediate selection strategy, which we call “Keep-Best Reproduction (KBR)”, found solutions of lower cost for a variety of travelling salesman problems. In this paper, we study the effects of crossover and mutation probabilities on STDS as well as on KBR. We study the effect of recombination alone, mutation alone and both together. We compare the performance of the different selection strategies and discuss the environment that each selection strategy needs to flourish in. Overall, KBR is found to be the selection strategy of choice. We also present empirical evidence that suggests that KBR is more robust than STDS with regard to operator probabilities.

Topic Area

Evolutionary Computing Genetic Algorithms Search 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Kay Wiese
    • 1
  • Scott D. Goodwin
    • 1
  1. 1.Department of Computer ScienceUniversity of ReginaReginaCanada

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