Multiobjective optimization of simulated moving bed by tissue P system

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Multiobjective optimization of simulated moving bed by tissue P system

HUANG Liang; SUN Lei; WANG Ning; JIN Xiaoming

National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China

Received:2006-09-06 Revised:1900-01-01 Online:2007-10-28 Published:2007-10-28
Contact: HUANG Liang

基于一类组织P系统的模拟移动床的多目标优化

黄亮; 孙磊; 王宁; 金晓明

National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China

通讯作者: 黄亮

Abstract

Abstract: The binaphthol enantiomers separation process using simulation moving bed technology is simulated with the true moving bed approach (TMB). In order to systematically optimize the process with multiple productive objectives, this article develops a variant of tissue P system (TPS). Inspired by general tissue P systems, the special TPS has a tissue-like structure with several membranes. The key rules of each membrane are the communication rule and mutation rule. These characteristics contribute to the diversity of the population, the conquest of the multimodal of objective function, and the convergence of algorithm. The results of comparison with a popular algorithm—the non-dominated sorting genetic algorithm 2(NSGA-2) illustrate that the new algorithm has satisfactory performance. Using the algorithm, this study maximizes synchronously several conflicting objectives, purities of different products, and productivity.

Key words: simulated moving bed, tissue P systems, multiobjective optimization, Pareto optimality, evolutionary algorithm, binaphthol enantiomers separation process

摘要： The binaphthol enantiomers separation process using simulation moving bed technology is simulated with the true moving bed approach (TMB). In order to systematically optimize the process with multiple productive objectives, this article develops a variant of tissue P system (TPS). Inspired by general tissue P systems, the special TPS has a tissue-like structure with several membranes. The key rules of each membrane are the communication rule and mutation rule. These characteristics contribute to the diversity of the population, the conquest of the multimodal of objective function, and the convergence of algorithm. The results of comparison with a popular algorithm—the non-dominated sorting genetic algorithm 2(NSGA-2) illustrate that the new algorithm has satisfactory performance. Using the algorithm, this study maximizes synchronously several conflicting objectives, purities of different products, and productivity.

关键词: simulated moving bed;tissue P systems;multiobjective optimization;Pareto optimality;evolutionary algorithm;binaphthol enantiomers separation process

HUANG Liang, SUN Lei, WANG Ning, JIN Xiaoming. Multiobjective optimization of simulated moving bed by tissue P system[J]. , DOI: .

黄亮, 孙磊, 王宁, 金晓明. 基于一类组织P系统的模拟移动床的多目标优化[J]. , DOI: .

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