Solving Cooperative Anti-Missile Weapon-Target Assignment Problems using Hybrid Algorithms based on Particle Swarm and Tabu Search

Abstract

Taking soft and hard weapon of a single warship cooperative anti-missile as background, under the fully research on the shipboard hard and soft weapon layered defense model, the firepower unit correlation matrix is put forward, which could simplify the problem complexity, minimizing the negative impact of the combination of firepower units while fighting against the same direction incoming missile targets. At the same time, in traditional weapon-target assignment, the maximum probability of joint damage or the minimum total expected survival rate of the target is usually set as the optimization goal, which result in firepower resources great waste. Aim to this problem, the minimum resource consumption model is established as the optimization goal, and we take the kill probability to the targets as an important constraint condition. The value of kill probability to each target can be set according to the incoming targets threaten degree and the firepower resources consumption. The minimum resource consumption model is solved by the hybrid optimized algorithm based on particle swarm and tabu search, the simulation results show that this method is more reasonable and feasible, in line with the realistic scenarios due to the algorithm could stop calculate at any time and give the current best solution.