一种利用膜计算求解高维函数的全局优化算法

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。

Algorithm for solving global optimization problems of multi-dimensional function based on membrane computing

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.