自适应PBIL算法求解一类动态优化问题

在不确定环境中,环境的变化总是以一定的概率发生,本文把何时变化看作随机变量,其满足一定的统计规律,由此归纳出一类动态优化问题。对于此类动态优化问题的求解,提出了自适应PBIL(Population-based incremental learning algorithm)算法。算法中利用随机变量的概率自适应地调整当前代群体的概率模型,增加种群多样性,快速适应环境的变化。应用两个动态优化问题进行了仿真实验。实验结果表明,与传统PBIL算法相比,自适应PBIL算法能够快速跟踪最优解的变化。

Adaptive PBIL algorithm for a class of dynamic optimization problems

In an uncertain environment,the environmental changes always occur with probabilities.In this paper the moment when a change occurs is considered as a random variable,which obeys certain distribution,and the dynamic problems possess such features are classified as a class of dynamic optimization problems.Then an adaptive population-based incremental learning(PBIL) algorithm is proposed to solve the class of dynamic optimization problems.This algorithm applies the adaptive probability of random variable to r...