Application of Heuristic Methods for Polymer Synthesis Process Optimization

Abstract

A numerical algorithm has been developed for solving the problem of finding optimal conditions for the synthesis of polymers using heuristic optimization methods, and its effectiveness has been evaluated in the investigation of the copolymerization process of butadiene with styrene, proceeding via a free-radical mechanism. To address the task of finding optimal synthesis conditions, a genetic algorithm has been proposed, and the main stages of its implementation using software development tools have been defined. For the mathematical description of the process, a kinetic approach based on the use of statistical moments of the molecular mass distribution has been employed, allowing for the derivation of a classical model description of the process in the form of a system of differential equations. Application of the genetic algorithm to this process has enabled the identification of the optimal regulator feeding regime, facilitating the attainment of the desired molecular product characteristics. The proposed algorithm is versatile, allowing for the search of one or multiple system parameters in both continuous and discrete variable sets, characteristic of optimizing technological parameters in industrial production.