Efficiently Immune Genetic Algorithm for Solving Cooperative Jamming Problem

This paper provides a mathematical model for cooperative jamming weapon target assignment problem. The existing intelligent optimization algorithms have two defects, i.e., with the scale of the problem increases, the quality of the solutions obtained by existing algorithms decreases and the calculate time the algorithms spent to find the optimal solutions becomes unacceptable. Therefore, an efficient immune genetic algorithm is proposed in this paper. In the proposed algorithm, an extended decimal coding scheme, an immune mechanism based roulette wheel selection operator, and a greedy repair operator are designed. Simulation experimental results indicate that the proposed algorithm is more efficient and effective than its competitors, and it can obtain optimal solutions with highly quality within acceptable time.