基于禁忌搜索与微粒群优化算法的混合优化策略算法在目标分配问题上的应用

Application of Hybrid Optimization Strategy Algorithm Based on Tabu Search and Particle Swarm Optimization Algorithms for Weapon-target Assignment Problems

目标分配是地面防空作战指挥的关键环节。给出问题模型,并提出一种禁忌搜索与改进微粒群算法的混合优化策略用于解决该问题。仿真结果表明,与其它几种智能优化算法相比,该混合优化策略在解决目标分配问题时具有优良的优化性能和时间性能,在问题规模较大时表现更为突出。

The weapon-target assignment（WTA） is very important to ground air-defense command systems.The math model of WTA was established.A novel hybrid optimization strategy（HOS） algorithm,based on particle swarm optimization（PSO） and tabu search（TS） algorithms was proposed to solve WTA problems.The simulation result shows that,compared with other algorithms,the HOS algorithm is excellent in the optimization performance and time performance in WTA,especially,in solving large-scale problems.