基于自适应变异粒子群算法的火力分配方法研究

针对最优火力分配的特点，分析了火力分配优化问题的数学模型，设计了一种求解该类问题的自适应变异粒子群算法（Adaptive Mutation Particle Swarm Optimization, AMPSO）。该算法采用十进制编码方法和基于数值运算的个体更新方法；为平衡算法的局部搜索能力和全局收敛性能，设计了一种关键参数自适应调整方法；为增强种群在进化后期的多样性，提出了一种变异策略。仿真结果表明，所提AMPSO算法具有良好的寻优性能，是优化火力分配的一种有效算法。

Study on Firepower Optimum Distribution Approach Based on Adaptive Mutation Particle Swarm Optimization

According to the principle of firepower optimum distribution, the mathematics model of firepower distribution problem is analyzed, whereas an improved particle swarm optimization ( AMPSO ) to this problem is designed. A decimalist encoding method and a particle update strategy based on numerical value operation are introduced, a dynamic adjusting strategy of key parameters is introduced to balance the local searching ability and global convergence performance, whereas a mutation strategy is proposed to In order to enhance the diversity of populations in the later evolution. The result of simulation experiment indicates the efficiency of the AMPSO, whereas the rationality of firepower distribution scheme gained are demonstrated.