面向进攻的武器-目标分配问题是军事运筹学研究中的重要课题,旨在制定合理的打击策略以最大程度摧毁敌方目标。采用一种融合局部搜索和信息素控制的蚁群算法,兼顾控制解的局部收敛速度和全局收敛质量。在解的构造过程中直接处理约束条件,提高生成解的可行性,并大大缩小了搜索空间,提高了算法效率。通过采用多种算法对不同规模的武器-目标分配问题进行实验,结果表明改进的蚁群算法在收敛速度和求解质量上表现优异。
The attack-oriented Weapon-Target Assignment(WTA) problem is an important subject in military operations research.The object of WTA is to obtain desirable engagement plans to maximize the damage of hostile targets.In this paper,we present an improved ant colony algorithm,incorporating local search and pheromone control mechanism,to accelerate local search and improve the quality of global convergence.We achieve constraint handling directly in the process of constructing WTA solutions,which enhances the feasibility of generated solutions and largely reduces search space.We applied different algorithms to various scales of WTA problems,and the results demonstrate that the improved ant colony algorithm has outstanding performance.