International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Adaptive Control of Strong Mutation Rate and Probability for Queen-bee Genetic Algorithms

  • Jung, Sung-Hoon (Department of Information and Communications Engineering, Hansung University)
  • Received : 2011.10.06
  • Accepted : 2011.11.03
  • Published : 2012.03.25
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Abstract

This paper introduces an adaptive control method of strong mutation rate and probability for queen-bee genetic algorithms. Although the queen-bee genetic algorithms have shown good performances, it had a critical problem that the strong mutation rate and probability should be selected by a trial and error method empirically. In order to solve this problem, we employed the measure of convergence and used it as a control parameter of those. Experimental results with four function optimization problems showed that our method was similar to or sometimes superior to the best result of empirical selections. This indicates that our method is very useful to practical optimization problems because it does not need time consuming trials.

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