基于一类组织P系统的模拟移动床的多目标优化

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.

Multiobjective optimization of simulated moving bed by tissue P system

The binaphthol enantiomers separation process using simulation moving bcd 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.