摘要
Based on the principles of Genetic Algorithms (GAs), a hybrid genetic algorithm used to optimize simple distillation column sequences was established. A new data structure, a novel arithmetic crossover operator and a dynamic mutation operator were proposed. Together with the feasibility test of distillation columns, they are capable to obtain the optimum simple column sequence at one time without the limitation of the number of mixture components, ideal or non-ideal mixtures and sloppy or sharp splits. Compared with conventional algorithms, this hybrid genetic algorithm avoids solving complicated nonlinear equations and demands less derivative information and computation time. Result comparison between this genetic algorithm and Underwood method and Doherty method shows that this hybrid genetic algorithm is reliable.
Based on the principles of Genetic Algorithms(GAs),a hybrid genetic algorithm used to optimize simple distillation columnsequences was established.A new data structure,a novel arithmetic crossover operator and a dynamic mutation operator were pro-posed.Together with the feasibility test of distillation columns,they are capable to obtain the optimum simple column sequence at onetime without the limitation of the number of mixture components,ideal or non-ideal mixtures and sloppy or sharp splits.Compared withconventional algorithms,this hybrid genetic algorithm avoids solving complicated nonlinear equations and demands less derivative infor-mation and computation time.Result comparison between this genetic algorithm and Underwood method and Doherty method shows thatthis hybrid genetic algorithm is reliable.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2004年第3期321-328,共8页
Computers and Applied Chemistry
关键词
化工计算
遗传算法
蒸馏柱
分离次序
最优化
genetic algorithms
distillation column sequence
chemical computation