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Probability distribution based recombination operator to solve unimodal and multi-modal problems

The neighborhood-based crossover operators used in real coded genetic algorithm (RCGA) are based on some probability distribution. It is observed that each crossover operator directs the search towards a different zone in the neighborhood of the parents. The quality of the elements that belong to the visited region depends on the particular problems to be solved. Different crossover operators perform differently with respect to the problems, even at the different stages of the genetic process in the same problem. In this paper, the role of probability distribution is empirically investigated on unimodal and multi-modal test problems. It is observed that the operator based on polynomial distribution achieves superior performance on unimodal test problems. The lognormal distribution based operator is efficient in solving multi-modal problems.