A hybrid optimization method (GA/SQP) for methyl acetate production process by reactive batch distillation

Abstract

The initialization problem of classical optimization techniques (for instance, Sequential Quadratic Programming) is generally crucial for the robustness of the code. This paper presents a contribution to handle this kind of problems by implementation of a hybrid optimization technique based on the successive use of a Genetic Algorithm (GA) and of a classical Sequential Quadratic Programming (SQP) method: the GA is used to perform a first search in the solution space and to locate the neighbourhood of the solution. Then, the SQP method is employed to refine the solution. The optimization of methyl acetate production process by reactive batch distillation serves as an illustration to validate the approach.