A genetic algorithm with multiple crossover operators for optimal frequency assignment problem

Abstract

A genetic algorithm employing multiple crossover operators in its implementation is presented. A set of available crossover operators is established initially and a particular crossover operator is probabilistically selected from this set for recombination. Each crossover operator is assigned a fitness value based on the amount fitness improvements they achieve over a number of previous generations. Hence, a randomized dynamic operator selection scheme is followed. This approach is used for the solution of the well-known frequency assignment problem for which optimal results are achieved in reasonable computation times even for the very difficult problem instances.