Multiobjective Optimization of Simulated Moving Bed by Tissue P System  

作　　者：黄亮 孙磊 王宁 金晓明 

机构地区：[1]National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University Hangzhou 310027, China

出　　处：《Chinese Journal of Chemical Engineering》2007年第5期683-690,共8页中国化学工程学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China （No.60421002）

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.用移动床技术的模拟的双性人萘粉 enantiomers 分离过程与真移动床途径(TMB ) 被模仿。以便系统地与多重生产目的优化这个过程，这篇文章开发织物 P 系统(TPS ) 的变体。由一般织物 P 系统启发了，特殊 TPS 与几膜有像织物的结构。每膜的关键规则是通讯规则和变化规则。这些特征贡献人口的差异，征服算法的客观功能，和集中多模式。有一个流行算法的比较的结果—非统治的排序的基因算法(NSGA-2 ) 2 说明新算法有令人满意的性能。用算法，这研究同时地最大化几冲突目的，不同产品的纯净，和生产率。

关 键 词：simulated moving bed tissue P systems multiobjective optimization Pareto optimality evolutionary algorithm binaphthol enantiomers separation process 

分 类 号：O65[理学—分析化学]