文献类型：期刊文献

英文题名：Hybrid gradient particle swarm optimization for dynamic optimization problems of chemical processes

作者：Chen, Xu[1];Du, Wenli[1];Qi, Rongbin[1];Qian, Feng[1];Tianfield, Huaglory[2]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Glasgow Caledonian Univ, Sch Engn & Built Environm, Glasgow G4 0BA, Lanark, Scotland

年份：2013

卷号：8

期号：5

起止页码：708

外文期刊名：ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING

收录：;EI(收录号：20134316901421);WOS:【SCI-EXPANDED(收录号:WOS:000325608600009)】；

基金：We are very grateful to the editor and anonymous reviewers for their valuable comments and suggestions to help improve our paper. This work is supported by Major State Basic Research Development Program of China (2012CB720500), National Natural Science Foundation of China (Key Program: 61134007), National Science Fund for Outstanding Young Scholars (61222303), National Natural Science Foundation of China (21276078, 21206037) and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：dynamic optimization; particle swam optimization; gradient-based algorithms; control vector parameterization; industrial process optimization

摘要：Dynamic optimization problems (DOP) in chemical processes are very challenging because of their highly nonlinear, multidimensional, multipeak and constrained nature. In this paper, we propose a novel algorithm named hybrid gradient particle swarm optimization (HGPSO) by hybridizing particle swarm optimization (PSO) with gradient-based algorithms (GBA). HGSPO can improve the convergence rate and solution precision of pure PSO, and avoid getting trapped to local optimums with pure GBA search. We further incorporate HGPSO into control vector parameterization (CVP), a method converting DOP into nonlinear programming, to solve five complex DOPs. These DOPs include multimodal, multidimensional and constrained problems. The experiments demonstrate that HGPSO performs much better in terms of solution precision and computational cost when compared with other PSO variants. (c) 2013 Curtin University of Technology and John Wiley & Sons, Ltd.