基于自适应变异规则的一种有效的进化规划

Efficient evolutionary programming based on a self-adaptive mutation rule

为改善普通进化规划的算法性能 ,通过学习进化过程中获得的种群整体进化信息 ,提出进化规划的一种新的自适应变异规则。基于该规则的进化规划不仅能加快算法的收敛速度 ,而且能有效地保证种群的多样性。用该方法可求解具有多个极值点的函数优化问题 。

To improve the efficiency of evolutionary programming, a self adaptive mutation rule is proposed by learning the evolutionary information of total population.With the novel mutation rule, evolutionary programming algorithm not only keeps the population diversity, but also has quicker convergence speed. It is applied to optimize functions with multi modal.The validity of the algorithm is shown by computer simulation results.