文献类型：期刊文献

英文题名：Alopex-based evolutionary algorithm and its application to reaction kinetic parameter estimation

作者：Li, Shaojun[1];Li, Fei[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

年份：2011

卷号：60

期号：2

起止页码：341

外文期刊名：COMPUTERS & INDUSTRIAL ENGINEERING

收录：;EI(收录号：20110413627687);WOS:【SCI-EXPANDED(收录号:WOS:000287290100016)】；

基金：This work was supported by National Natural Science Foundation of China (under Project No. 20976048) and Shanghai Leading Academic Discipline Project (under Project No. B504). And we would like to thank anonymous referees for their helpful comments and suggestions. Their rigorous academic attitude and detailed review lead to a significant improvement of the manuscript.

语种：英文

外文关键词：Evolutionary algorithm; Alopex; Probability; Simulated annealing; Parameter estimation

摘要：In this paper, a novel Alopex-based evolutionary algorithm (AEA) is proposed, whose distinguished features are stochastic selection and self-adaptive evolutionary computation. The AEA not only inherits the primary characteristics of basic evolutionary algorithms (EAs), but also possesses the merits of gradient methods and simulated annealing algorithm. It can efficiently maintain the population diversity and improve the capabilities of escaping from local optima. The numerical simulation results of 22 benchmark functions demonstrate that the performance of the proposed AEA is superior to that of the basic EAs. Finally, the new algorithm is applied to estimate the kinetic parameters of 2-chlorophenol oxidation of supercritical water. The promising results illustrate the efficiency of the proposed method and show that it could be used as a reliable tool for engineering applications. (C) 2010 Elsevier Ltd. All rights reserved.