摘要
鉴于传统优化算法在求解高维多模态优化问题时存在收敛速度慢,求解精度低的缺点,针对上述问题提出了一种基于膜计算的优化算法。算法首先对高维空间进行分割,分割后每个子空间作为一个基本膜,基本膜区域中采用差分局部搜索策略提高算法的局部搜索能力和收敛速度。基本膜区域将局部最优解定时传送给表层膜。表层膜区域中采用全局搜索策略寻找全局最优解。通过对5个benchmark函数仿真验证,实验结果表明,该算法在收敛速度,求解精度和稳定性方面都有较大优势。
Traditional differential evolution algorithm exists shortcoming,such as trapping into local optimum easily,low convergence speed and solution precision.This paper presents an optimization algorithm for solving global optimization problems of multi-dimensional function based on membrane computing.With this algorithm,high dimension space is segmented some subspaces and each subspace is an elementary membrane.In elementary membrane,differential evolution algorithm is used to do local search strategy which enhances the searching ability and accelerates the convergent speed.At the same time,local optimal solutions in the elementary membrane are sent to outermost membrane and the outermost membrane searchs the global optimal solutions with global search strategy.The experimental test indicates the algorithm has the advantages of fine stability, fast convergence speed and high precision and can get the global optimal solutions.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第19期27-30,共4页
Computer Engineering and Applications
基金
国家高技术研究发展计划(863)No.2008AA01A303
陕西理工学院青年科研基金项目(No.SLG0818)
陕西省教育厅科研项目(No.2010JK459
No.2010JK466)~~
关键词
膜计算
高维多模
全局优化
差分进化
membrane computing
multi-dimensional function
global optimization
differential evolution
