Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5875
Title: Adaptive non-uniform crossover based on statistics for genetic algorithms
Authors: Yang, S
Issue Date: 2002
Publisher: Morgan Kaufmann Publishers Inc
Citation: Genetic and Evolutionary Computation Conference (GECCO 2002), San Francisco, CA, USA: 650 - 657, 2002
Abstract: Through the population, genetic algorithm (CA) implicitly maintains the statistics about the search space. This implicit statistics can be used explicitly to enhance GA's performance. Inspired by this ides, a statistic based adaptive non-uniform crossover, called SANUX, has been proposed. SANUX uses the statistics information of the alleles in each locus information 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 instead 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 Morgan Kaufmann Publishers Inc
URI: http://bura.brunel.ac.uk/handle/2438/5875
ISBN: 1-55860-878-8
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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