改进的正态分布的分布估计算法

Improved Estimation of Distribution Algorithms Based on Normal Distribution

针对连续空间函数优化问题,提出了改进的正态分布的分布估计算法。该算法将优选出的个体看作正态分布,然后以正态分布概率模型随机采样产生新的种群,并挑选部分个体与保留的最好解进行交叉操作。将其与均匀分布的分布估计算法、正态分布的分布估计算法进行了比较,结果证明该方法的效果更好。最后分析了选择较好个体的比例对算法的影响。

An improved estimation of distribution algorithm based on normal distribution was presented for function op-timization in continuous space. The algorithm regards the selected individual as a normal distribution, and the ranclom new populations of normal distribution are generated, and some selected individuals are crossed with the best solution. Compared with estimation of distribution algorithm based on uniform distribution and estimation of distribution algo- rithm based on normal distribution, the improved estimation of distribution algorithm based on normal distribution is more effective through result. At last, the influence of better population selection proportions was analyzed.