A new strategy for the application of genetic algorithms to the channel-assignment problem

The channel-assignment problem in cellular radio networks is known to belong to the class of NP-complete optimization problems. So far, this problem has been solved by heuristic assignment strategies or by the application of combinatorial optimization tools like simulated annealing or neural networks. We propose a new powerful approach to the channel-assignment problem by combining the two mentioned groups of solution techniques. The results obtained by the application to a well-known benchmark problem reveal that this absolutely new strategy clearly outperforms the already existing algorithms.