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

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 of 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 for which optimal results are achieved in reasonable computation times even for the very difficult problem instances.