Weapon-target Assignment Based on Improved Particle Swarm Optimization for Different Allocation Criteria

In this paper, weapon-target assignment (WTA) mathematical models for various allocation criteria are built, and a fast WTA optimization algorithm is proposed. By introducing the target threat assessment, missile interception probability and target time-to-go, five allocation criteria are designed, which are i) maximum intercept probability criterion, ii) reaching intercept probability threshold criterion, iii) fast and high-probability intercept criterion, iv) maximum cost-effectiveness criterion, and v) target-threat-priority based stochastic assignment criterion. Based on those criteria, the WTA problem is formulated as a zero-one integer programming problem, with considering multiple assignment constraints. Furthermore, an improved heuristic-swarm-intelligence optimization algorithm is proposed, which combines the particle swarm optimization and the simulated annealing to solve WTA problem efficiently. Also, the performance indexes are built for evaluating WTA optimization results. Numerous simulation results demonstrate the effectiveness of the proposed optimization algorithm, and show its advantage in searching global optimal solution. Meanwhile, each criterion achieves best performance in a specified scenario with considering related task requirements and weapon resources.