混沌伪并行遗传算法及其在火力分配优化中的应用

Chaos Pseudo Parallel Genetic Algorithm and Its Application on Fire Distribution Optimization

  • 摘要: 剖析了混沌模型的随机性、遍历性和初值敏感性的特点,提出了多种群伪并行混沌遗传算法.把多群体伪并行进化的并行性和混沌运动的内在随机性结合起来,利用不同的混沌扰动策略,把混沌变尺度映射机理应用到种群初始化和中间群体的优化进化实现函数优化.仿真结果表明,混沌伪并行遗传算法比伪并行遗传算法和简单遗传算法具有更快的收敛速度和更高的最优解搜索成功率,可对火力分配进行优化.

     

    Abstract: Analyzes the stochastic ergodicity and sensitivity of initial value of chaos model,proposes the chaos pseudo parallel genetic algorithm(CPPGA) based on multiple populations.Combines the parallel character of multiple population pseudo parallel evolution with inner stochastic character of chaos movement,applying different chaotic disturbance strategies,taking chaos' variable measure map mechanism into population initialization or middle populations fulfilled function optimization.Simulation results showed that CPPGA improved the convergence velocity and search probability of optimization solution,and got good optimization strategy for fire distribution.

     

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