A Hybrid Genetic Algorithm for the Estimation of Polyesterification Kinetic Parameters

A simple genetic algorithm (SGA) has been improved in this paper. The resulting hybrid genetic algorithm (HGA) was used to estimate the kinetic parameters of polyesterification between dimer fatty acid and ethylene glycol. The acid values of product predicted by the kinetic model match well with experimental data at different material proportions and conversion ratios. The kinetic model was proven to be effective. The hybrid genetic algorithm was compared with the simple genetic algorithm, and the result indicated that the improved genetic algorithm has higher efficiency, stronger ability on local searches, better precision, and a wider search range. Parameters of the polyesterification kinetic model were estimated by the Hybrid Genetic algorithm (HGA), the model predicted data matches well with the experimental data. The HGA obtained the preferred parameters more quickly and accurately than a simple genetic algorithm (SGA).