Stochastic GP synthesis of heat integrated nonsharp distillation sequences

Genetic programming (GP) is used to solve the synthesis problem of heat integration nonsharp distillation sequences and the optimization objective of it is to seek the optimal heat integration nonsharp flow based on minimizing the annually total cost. Meanwhile, the major technological parameters for these important equipments are given. Combining with the domain knowledge of chemical engineering, some evolutionary factors are improved, and a set of special encoding method and heat integration strategy is proposed to deal with this kind of problem. The system structural variable is optimized by GP and the continuous variable is optimized by the complex algorithm simultaneously. Because GP has the automatically searching function, the optimal heat integration solution can be found automatically without any superstructures of nonsharp distillation sequences. Three illustrating examples are presented to demonstrate the effective computational strategies.