Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A Normed Space of Genetic Operators with Applications to Scalability Issues
Evolutionary Computation
Schemata evolution and building blocks
Evolutionary Computation
Effects of population size on the performance of genetic algorithms and the role of crossover
Artificial Life and Robotics
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By applying the schema theorem, we study the effects of crossover in Genetic Algorithms with the multiplicative fitness function. On this landscape, the analytical expression of the exact schema theorem can be obtained, and this makes it possible to carry out the mathematical investigation of genetic operators. We consider the average fitness under the action of selection, mutation and crossover. To do this, we give the expressions for the average and variance of fitness in terms of schema frequencies. The theoretical results are compared with numerical experiments.