文献类型：期刊文献

英文题名：A multi-population cultural algorithm with adaptive diversity preservation and its application in ammonia synthesis process

作者：Xu, Wei[1,2];Wang, Raofen[1];Zhang, Lingbo[1];Gu, Xingsheng[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China

年份：2012

卷号：21

期号：6

起止页码：1129

外文期刊名：NEURAL COMPUTING & APPLICATIONS

收录：;EI(收录号：20123615406550);WOS:【SCI-EXPANDED(收录号:WOS:000307552600006)】；

基金：We are very grateful to the editors and anonymous reviewers for their valuable comments and suggestions to help improve our paper. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2009AA04Z141), National Natural Science Foundation of China (Grant no. 61174040), Shanghai Commission of Science and Technology (Grant no. 08JC1408200), Shanghai Leading Academic Discipline Project (Grant no. B504), and the Specialized Research Fund for Doctoral Program of Higher Education of China (No. 200802510010).

语种：英文

外文关键词：Cultural algorithm; Differential evolution; Knowledge exchange; Adaptive diversity preservation; Ammonia synthesis

摘要：A multi-population cultural differential evolution (MCDE) algorithm is proposed. Each of the populations is managed by its private cultural differential evolution algorithm, in which a center individual is introduced into the belief space and selection function follows a new method to select the offspring for the next generation. To accelerate the convergence speed, the populations exchange their knowledge with each other every given generations. An adaptive mechanism of population diversity preservation is put forward to prevent the populations from being trapped in local optima. In the adaptive mechanism, the idea of culture fusion between populations is used to know the convergence status, so that the diversity of populations is kept along the evolutionary process. The performance evaluation on MCDE using eleven constrained optimization problems shows that MCDE is a competitive approach. MCDE is further applied to a practical optimization problem in an ammonia synthesis system with the objective to maximize the net value of ammonia. The results achieved by MCDE are compared with those by two traditional differential evolution algorithms, which indicate that MCDE has more excellent performance and better effectiveness.