Large-Scale Weapon Target Assignment Based on Improved MOEA/D Algorithm

In this paper, a modified MOEA/D algorithm with wider spread of solutions and faster convergence rate is developed to solve the static weapon target assignment problem. First, a bi-objective static weapon target assignment model is proposed for large-scale heterogeneous missile clusters and large- scale multi type targets assignment. Second, a decimal encoding method is designed to discribe multi-type weapons, where the population is updated by using the crossover and mutation operators and a repair operator is designed to rectify new generation. Third, the normalized Tchebycheff approach is adpoted to solve the problem of the difference of bi-objective scale. Finally, the advantage of the modified algorithm is illustrated by some numerical experiments.