Genetic Algorithms Approach to the Channel Assignment Problem

The optimal assignment problem of channels has become increasingly important since the usable range of the frequency spectrum is limited. Recently Genetic Algorithms (GAs) have been proposed as new computational tools for solving optimization problems. GAs are more attractive than other optimization techniques, such as neural network or simulated annealing, since GAs are generally good at nd-ing acceptably good global optimal solution to a problem very quickly. In this paper, a new channel assignment algorithm using GAs is proposed. The channel assignment problem is formulated as an energy minimization problem that is implemented by GAs. Appropriate GAs operators such as reproduction , crossover and mutation are developed and tested. In this algorithm, the cell frequency is not xed before the assignment procedures as in the previously reported channel assignment algorithm using neural networks. All three constraints are also considered for the channel assignments: the co-channel constraint, the adjacent channel constraint and the co-site channel constraint. The goal of this paper is the assignment of the channel frequencies which satissed these constraints with the lower bound number of channels.