关键词: 基于量子行为的粒子群优化算法(QPSO},粒子聚集度，慢变函数，武器目标分配CWTA}

Abstract: In order to improve the solving efficiency and performance of weapon target assignment (WI'A)，this paper put forward a kind of improved quantum-behaved particle swarm optimization algorithm for solving WTA. First, based on the particle aggregation premature stagnation was judged. Then a slowly varying function was used to overcome pre- mature convergence while keeping the population diversity. Secondly, a multiple weapons target assignment was built to meet the target of the minimum failure probability in allocating weapons and shooting all targets. Simulation results in- dicate that the new algorithm can get the optimal or suboptimal solution to WTA problems, effectively solve }门A problems.

Key words: Quantum-behaved particle swarm optimization, Particle aggregation, Slowly varying function, Weapon target asstgnrrtent