A Mutation-Based GA for Weapon-Target Allocation Problem Subject to Spatial Constraints

In the actual weapon-target allocation (WTA) problem, weapons are always widely dispersed and they have limited launch zone so that an incoming target will not be enclosed in the range of all weapons. Subject to the spatial constraints of the WTA problem, the weapons can not be paired with the targets randomly. In this paper a genetic algorithm (GA) based method is developed to solve the considered WTA problem, where a chromosome is encoded as binary matrix with "forbidden bits" to represent the constraints. A novel "circle-swap" operator is proposed, as a functional mutation operator for the matrix-type chromosome with forbidden bits, which can guarantee the validity of the chromosome as a solution all through the evolving process. Simulation results verify the feasibility of the mutation-based GA.