基于CE-CAPSO武器目标分配优化算法
Optimization Algorithm for Weapon Target Assignment Based on CE-CAPSO
为了提高求解武器目标分配问题算法的效率和准确性,避免算法迭代陷入局部最优解,引入云自适应模型和鲶鱼效应思想,改进基本粒子群算法;建立了符合实际的WTA模型,分别使用PSO、CAPSO、CE-CAPSO、改进CE-CAPSO、改进遗传算法对模型求解,仿真结果表明,改进的粒子群算法在求解准确性、稳定度和收敛速度有明显提升,验证了方法的有效性和实用性。
In order to improve the efficiency and correctness of the algorithm for solving weapon target assignment problem and avoid iteration falling into local optimum solution,cloud adaptive model and the thought of catfish effect are introduced to improve the basic particle swarm optimization algorithm,and practical WTA models are established,which are solved by PSO,CAPSO,CE-CAPSO and improved CE-CAPSO respectively. The simulation results show that the correctness,stability and convergence speed of the improved particle swarm optimization algorithm are significantly improved,which verifies the effectiveness and practicability of the method.
WTA; cloud model; PSO; catfish effect;
E91;TP18
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