Zhang Ziyang, Mazzotti M, Morbidelli M. Multiobjective optimization of simulated moving bed and varicol processes using a genetic algorithm [J]. J. Chromatogr. A, 2003, 989(1): 95-108
[2]
Kurup A S, Hidajat K, Ray A K. Optimal operation of an industrial-scale parex process for the recovery of p-xylene from a mixture of C8 aromatics [J]. Ind. Eng. Chem. Res., 2005, 44(15): 5703-5714
[3]
Wu Xiandong(吴献东), Jin Xiaoming(金晓明), Su Hongye(苏宏业). Multi-objective optimization of simulated moving bed chromatography separation based on NSGA-Ⅱ algorithm [J]. Journal of Chemical Industry and Engineering (China)(化工学报), 2007, 58(8): 2038-2044
[4]
Xiao Di(肖迪), Ge Qicheng(葛启承), Lin Jinguo(林锦国), Cheng Ming(程明). Double populations genetic and particle swarm algorithm and its application in SMB optimization [J]. Journal of Nanjing University of Science and Technology(南京理工大学学报), 2012, 36(1): 31-36
[5]
Huang Liang, Sun Lei, Wang Ning, Jin Xiaoming. Multiobjective optimization of simulated moving bed by tissue P system [J]. Chin. J. Chem. Eng., 2007, 15(5): 683-690
[6]
Nayak M R, Nayak C K, Rout P K. Application of multi-objective teaching learning based optimization algorithm to optimal power flow problem [J]. Procedia Technology, 2012, 6: 255-264
[7]
Pais L S, Loureiro J M, Rodrigues A E. Modelling strategies for enantiomers separation by SMB chromatography [J]. AIChE J., 1998, 44(3): 561-569
[8]
Yang Minglei(杨明磊), Wei Min(魏民), Hu Rong(胡蓉), Ye Zhencheng(叶贞成), Qian Feng(钱锋). Modeling of the simulated moving bed for xylene separation [J]. CIESC Journal (化工学报), 2013, 64(12): 4335-4341
[9]
Rao R V, Savsani V J, Vakharia D P. Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems [J]. Computer-Aided Design, 2011, 43(3): 303-315
[10]
Rao R V, Savsani V J, Vakharia D P. Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems [J]. Information Sciences, 2012, 183(1): 1-15
[11]
Niknam T. A new multi objective optimization approach based on TLBO for location of automatic voltage regulators in distribution systems [J]. Eng. Appl. Artif. Intell., 2012, 25(8): 1577-1588
[12]
Rao R V, Patel V. Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm [J]. Applied Mathematical Modeling, 2013, 37(3): 1147-1162
[13]
Ruthven D M, Ching C B. Counter-current and simulated counter-current adsorption separation process [J]. Chem. Eng. Sci., 1989, 44(5): 1011-1038
[14]
Pais L S, Loureiro J M, Rodrigues A E. Chiral separation by SMB chromatography [J]. Separation and Purification Technology, 2000, 20(1): 67-77
[15]
Minceva M, Rodrigues A E. Understanding and revamping of industrial scale SMB units for p-xylene separation [J]. AIChE J., 2007, 53(1): 138-149
[16]
Yu H W, Ching C B. Optimization of a simulated moving bed based on an approximated langmuir model [J]. AIChE J., 2002, 48(10): 2240-2246
[17]
Migliorini C, Mazzotti M, Morbidelli M. Robust design of counter-current adsorption separation process(5): Nonconstant selectivity [J]. AIChE J., 2000, 46(7): 1384-1399
[18]
Minceva M, Rodrigues A E. Modeling and simulation of a simulated moving bed for the separation of p-xylene [J]. AIChE J., 2007, 53(1): 138-149
[19]
Storti G, Mazzotti M, Morbidelli M. Robust design of binary countercurrent adsorption separation processes [J]. AIChE J., 1994, 40(11): 1825-1842
[20]
Kawajiri Y, Biegler L T. Optimization strategies for simulated moving bed and powerfeed processes [J]. AIChE J., 2006, 52(4): 1343-1350
