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Selection Based on the Pareto Nondomination Criterion for Controlling Code Growth in Genetic Programming

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Abstract

The rapid growth of program code is an important problem in genetic programming systems. In the present paper we investigate a selection scheme based on multiobjective optimization. Since we want to obtain accurate and small solutions, we reformulate this problem as multiobjective optimization. We show that selection based on the Pareto nondomination criterion reduces code growth and processing time without significant loss of solution accuracy.

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Authors and Affiliations

  1. Computer and Automation Research Institute, Hungarian Academy of Sciences, 1518, Budapest, P.O.B. 63, Hungary

    Anikó Ekárt

  2. Computer and Automation Research Institute, Hungarian Academy of Sciences, 1518, Budapest, P.O.B. 63, Hungary

    S. Z. Németh

Authors
  1. Anikó Ekárt
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  2. S. Z. Németh
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Ekárt, A., Németh, S.Z. Selection Based on the Pareto Nondomination Criterion for Controlling Code Growth in Genetic Programming. Genetic Programming and Evolvable Machines 2, 61–73 (2001). https://doi.org/10.1023/A:1010070616149

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