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Mutation by imitation in boolean evolution strategies

  • Modifications and Extensions of Evolutionary Algorithms Genetic Operators and Problem Representation
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Parallel Problem Solving from Nature — PPSN IV (PPSN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1141))

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Abstract

Adaptive heuristics have been developed in the Evolution Strategy (ES) frame regarding the mutation of real-valued variables. But these heuristics poorly extend to discrete variables: when the rate or variance of mutation gets too small, mutation has no effect any more. To overcome this problem, we propose two mutation operators, that use the worst individuals of the current population as beacons indicating the limits of the current promising region:

Mutation by differentiation drives individuals away from the beacon individuals. Mutation by imitation inversely assumes that beacon-individuals still contain relevant informations, and aims at moving the indiidual at hand nearer to the beacons. Mutation by imitation produces offspring that share the features of several “parents”; but in contrast with classical crossover, it allows one to control the distance between the offspring and the main parent, by fixing the number of bits to mutate. Mutation by imitation thus permits a tunable exchange of informations among individuals.

Both operators have been implemented in a boolean (Μ + λ) ES framework, and experimented on four problems: the Royal Road problem, a GA-deceptive problem, the combinatorial multiple knapsack optimization problem and the Long Path problem. Comparative validation is presented and discussed.

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Author information

Authors and Affiliations

  1. Ecole Polytechnique, LMS - URA CNRS 317, 91128, Palaiseau Cedex, France

    Michèle Sebag

  2. Ecole Polytechnique, CMAP - URA CNRS 756, 91128, Palaiseau Cedex, France

    Marc Schoenauer

Authors
  1. Michèle Sebag
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  2. Marc Schoenauer
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Editor information

Hans-Michael Voigt Werner Ebeling Ingo Rechenberg Hans-Paul Schwefel

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© 1996 Springer-Verlag Berlin Heidelberg

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Sebag, M., Schoenauer, M. (1996). Mutation by imitation in boolean evolution strategies. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1000

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  • DOI: https://doi.org/10.1007/3-540-61723-X_1000

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61723-5

  • Online ISBN: 978-3-540-70668-7

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