Applying genetic algorithms to frequency assignment problems

This paper details the application of a parallel genetic algorithm to the air-ground-air frequency assignment problem. Preliminary results indicate that the technique is successful in finding acceptable assignments, satisfying over 90% of constraints, for realistically sized air- ground-air frequency assignment scenarios. Comparisons are made with a classical backtracking and forward checking heuristic algorithm which is shown to be inferior to the genetic algorithm in terms of the execution time required to find reasonable frequency assignments.