An analysis of the interacting roles of population size and crossover in genetic algorithms | Zendy

Kenneth De Jong | Zendy; William M. Spears | Zendy

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An analysis of the interacting roles of population size and crossover in genetic algorithms

Author(s) -

Kenneth De Jong,

William M. Spears

Publication year - 1991

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-54148-9

DOI - 10.1007/bfb0029729

Subject(s) - crossover , computer science , population , genetic algorithm , point (geometry) , population size , algorithm , mathematical optimization , artificial intelligence , mathematics , machine learning , demography , geometry , sociology

In this paper we present some theoretical and empirical results on the interactingroles of population size and crossover in genetic algorithms. We summarize recenttheoretical results on the disruptive effect of two forms of multi-point crossover: n-point crossover and uniform crossover. We then show empirically that disruptionanalysis alone is not sufficient for selecting appropriate forms of crossover. However,by taking into account the interacting effects of population size and...

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