Abstract
In this paper an abstract genetic algorithm (GA) is proposed which effectively merges local hill-climbing with recombination and population based selection in a general manner. This extension is possible because the traditional crossover can be resolved into two functions: one function is as a particular class of operator, which is actually distinct from the other which is the recombination itself. Thus traditional GAs can be classified as a special case of a more general approach in which recombination is applied along with other operators. In the work reported here, using the framework of an abstract GA, the performance of several operators as well as the effects of recombination are studied in the context of the graph bipartitioning problem.
This work was undertaken when the first author was with the Control Theory and Appplications Centre, Coventry University, UK
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References
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© 1995 Springer-Verlag/Wien
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Höhn, C., Reeves, C. (1995). Incorporating Neighbourhood Search Operators Into Genetic Algorithms. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_57
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_57
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
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