TY - JOUR
T1 - A framework for application of genetic algorithm to model-based design of reactive distillation process
AU - Lim, Kai Tun
AU - Matsumoto, Hideyuki
AU - Yamaki, Takehiro
AU - Matsuda, Keigo
PY - 2014
Y1 - 2014
N2 - In the present study, we investigate a framework for the application of genetic algorithm (GA) methods to reactive distillation (RD) process design. First, a computational method for hybrid simulation is proposed by linking a commercial process simulator with an in-house GA-based optimizer in order to accelerate the search for process designs showing high performance. When developing the hybrid simulation system, detailed methods for the GA operations of crossover, mutation, and selection were investigated to achieve a combination that maximizes the effectiveness of the simulation framework. Next, we investigate the designs obtained from the simulations for a case study, an RD process for acetyl acetate. The proposed GA method is shown to provide not only the lowest total annual cost (TAC) design, but also various alternative design solutions. Since the generation of alternative designs lets us consider many other factors, e.g., the distillate composition and the overall conversion of the product, we believe that the application of techniques such as multi-niche crowding (MNC) GA could be effective for searching simultaneously structural and operational conditions of multifunctional processes.
AB - In the present study, we investigate a framework for the application of genetic algorithm (GA) methods to reactive distillation (RD) process design. First, a computational method for hybrid simulation is proposed by linking a commercial process simulator with an in-house GA-based optimizer in order to accelerate the search for process designs showing high performance. When developing the hybrid simulation system, detailed methods for the GA operations of crossover, mutation, and selection were investigated to achieve a combination that maximizes the effectiveness of the simulation framework. Next, we investigate the designs obtained from the simulations for a case study, an RD process for acetyl acetate. The proposed GA method is shown to provide not only the lowest total annual cost (TAC) design, but also various alternative design solutions. Since the generation of alternative designs lets us consider many other factors, e.g., the distillate composition and the overall conversion of the product, we believe that the application of techniques such as multi-niche crowding (MNC) GA could be effective for searching simultaneously structural and operational conditions of multifunctional processes.
KW - Genetic algorithm
KW - Model-based design
KW - Optimization
KW - Reactive distillation
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U2 - 10.1252/jcej.13we119
DO - 10.1252/jcej.13we119
M3 - Article
AN - SCOPUS:84894268981
VL - 47
SP - 187
EP - 194
JO - Journal of Chemical Engineering of Japan
JF - Journal of Chemical Engineering of Japan
SN - 0021-9592
IS - 2
ER -