Efficiently solving multi-objective dynamic weapon-target assignment problems by NSGA-II

Abstract

A multi-objective dynamic weapon-target assignment (MODWTA) problem with three competing objectives, resource constraints, feasibility constraints and fire transfer constraints is studied in this paper. The weapon-target assignment (WTA) problem is formulated into a multi-objective constrained combinatorial optimization problem. Apart from maximizing damage to hostile targets, the research in this paper follows the principle of minimizing ammunition consumption and total operational time under the consideration of limited resource constraints, feasibility constraints and fire transfer constraints. Because of these competing objectives and rigorous constraints, the WTA problem becomes more complicated. In order to tackle the two challenges, the well-known non-dominated sorting genetic algorithm with elitist strategy, namely NSGA-II, is adopted according to the specific structure of the problem to achieve efficient problem solving. Besides, the proposed NSGA-II is compared with a multi-objective Monte Carlo random sampling method, which shows the superiority of the proposed MODWTA algorithm. The numerical simulation results show that the proposed NSGA-II algorithm effectively finds the approximate Pareto front within acceptable time.