基于分布式估计算法的群体智能优化

为了更好地求解连续函数最优化问题，对基于正态分布的分布式估计算法进行改进，在原算法的基础上引入优势替换、竞争和模式搜索等机制。为了验证所提策略和算法的有效性，对所提出的5种改进算法进行比较，证明改进的策略模块是有效的，相比现有算法能够收敛到更好的解。对5种算法进行数值仿真，求出每种函数在不同测试函数下30次实验后的平均适应值，以及描述算法稳定性的若干统计量。最后基于数值仿真的结果，对改进效果进行分析讨论。

Swarm Intelligence Optimization Based on Estimation of Distribution Algorithm

In order to solve the numerical optimization problem, the estimation of distribution algorithm based on normal distribution is researched and improved. On the basis of the existing algorithms, the replacement strategy with advantages, competing mechanism and pattern search are introduced. Compared with five kinds of improved algorithms, it is proved that the proposed strategies and the modified algorithms are effective and can find even better solutions. Finally, the effects of improvement are explained based on the numerical simulations and statistical analysis.