A Linear Mean-Field Annealing Algorithm Solving Weapon Target Assignment Problem

Traditional optimization algorithms have been applied to solve the Weapon Target Assignment (WTA) problem, but these algorithms usually solve small size instances. In this paper, we propose a linear mean-field algorithm with Hopfield network to solve large size assignments. This kind of algorithm that combines the advantage of neural network and simulated annealing can quickly converge to a global optimum solution. Compared with stochastic simulate annealing algorithm and mean-field annealing algorithm, some experimental results testify its feasibility.