Under this article, we offer a novel neural-network approach called gradual neural network (GNN) hybridized with a genetic algorithm for a class of combinatorial optimization problems of requiring the constraint satisfaction and the goal function optimization simultaneously. The hard problem of frequency assignment problem in the mobile communication system is efficiently solved by GNN as the typical problem of this class.The goal of this problem is to minimize the electromagnetic compatibility constraints between transceivers by first, rearranging the frequency assignment so that they can accommodate the increasing demands and second, using a minimum number of frequencies. An optimal solution is sought to facilitate the subsequent addition of new links. The binary neural network achieves the constraint satisfaction with the help of genetic algorithm, in order to seek the cost optimization and the network topology. The capability of the GNN algorithm is demonstrated through solving real instances in practical problem, showing that it can find far equivalent solutions than the existing algorithms, has good performance, and suggests a new interesting direction for research
