Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5889
Title: Statistics-based adaptive non-uniform crossover for genetic algorithms
Authors: Yang, S
Issue Date: 2002
Publisher: University of Birmingham
Citation: 2002 UK Workshop on Computational Intelligence (UKCI'02), Birmingham, U.K.: 201 - 208, 2- 4 Sep 2002
Abstract: Through the population, genetic algorithm (GA) implicitly maintains the statistics about the search space. This implicit statistics can be used explicitly to enhance GA's performance. Inspired by this idea, a statistics-based adaptive non-uniform crossover, called SANUX, has been proposed. SANUX uses the statistics information of the alleles in each locus to adaptively calculate the swapping probability of that locus for crossover. A simple triangular function has been used to calculate the swapping probability. In this paper two different functions, the trapezoid and exponential functions, are investigated for SANUX insteadd of the triangular function. The experiment results show that both functions further improve the performance of SANUX across a typical set of GA's test problems.
Description: Copyright @ 2002 University of Birmingham
URI: http://bura.brunel.ac.uk/handle/2438/5889
ISBN: 0704423685
9780704423688
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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