Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5980
Title: Adaptive crossover in genetic algorithms using statistics mechanism
Authors: Yang, S
Issue Date: 2002
Publisher: MIT Press
Citation: 8th International Conference on Artificial Life (ALife VIII): 182 - 185, 2002
Abstract: Genetic Algorithms (GAs) emulate the natural evolution process and maintain a popilation of potential solutions to a given problem. Through the population, GAs implicitly maintain 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 (SANUX) has been proposed. SANUX uses the statisics information of the alleles in each locus to adaptively caluclate the swapping probability of that locus for crossover operation. A simple triangular function has been used to calculate the swapping probability. In this paper new functions, the trapezoid and exponential functions, are proposed for SANUX instead of the triangular function. Experiment results show that both functions further improve the performance of SANUX.
Description: The final published version of this article is available at the link below. Copyright @ MIT Press.
URI: http://alife.org/alife8/proceedings/sub2412.pdf
http://bura.brunel.ac.uk/handle/2438/5980
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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