基于模糊罚函数的分布式并行遗传算法及其应用

Distributed parallel genetic algorithm based on fuzzy penalty function and its application in structural optimization

摘要: 本文将模糊理论用于优化中,提出了一种基于可行度的模糊罚函数法,并采用分布式并行遗传算法进行寻优操作,该方法可以将不同遗传操作的优点加以整合,通过并行运算提高优化效率.将基于模糊罚函数的分布式并行遗传算法应用到多目标结构优化中,仿真试验表明取得了很好的寻优效果.

Abstract: In this article,fuzzy theory is introduced in optimization and a new fuzzy penalty function based on feasible degree is presented.Distributed parallel genetic algorithm(DPGA) is proposed to search operation.This new algorithm integrates the optimums of different genetic operator,and uses parallel operation to improve the optimization efficiency.Then a satisfying performance is obtained.