Solving Weapon-Target Assignment Problems by Cultural Particle Swarm Optimization

Shaolei Wang, Weiyi Chen
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引用次数: 5

Abstract

The weapon-target assignment is a very complicated problem and a key point in the warship formations' air defense operation. In this paper, a cultural particle swarm optimization algorithm for solving WTA problems is proposed. The general idea of the proposed algorithm is to combine the advantages of PSO which integrates local search and global search scheme possesses high search efficiency, and that of cultural algorithm which combines the search method with the knowledge representation scheme for collecting and reasoning knowledge about individual experience to avoid premature convergence. An example is used to verify the correctness and effectiveness of the proposed cultural PSO algorithm, comparing with both the traditional PSO method and the genetic algorithm method. The simulation results demonstrate that the proposed algorithm has rapid convergence speed and higher solution precision.
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用培养粒子群算法求解武器目标分配问题
武器目标分配是一个非常复杂的问题,是舰艇编队防空作战中的一个关键问题。本文提出了一种求解WTA问题的文化粒子群优化算法。该算法的总体思想是将粒子群算法的优点结合起来,粒子群算法将局部搜索和全局搜索方案相结合,具有较高的搜索效率,而文化算法将搜索方法与知识表示方案相结合,可以收集和推理个人经验知识,避免过早收敛。通过与传统粒子群算法和遗传算法的比较,验证了所提文化粒子群算法的正确性和有效性。仿真结果表明,该算法具有较快的收敛速度和较高的求解精度。
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