Control of Continuous Polymer Synthesis Processes Using Heuristic Optimization Methods

This paper addresses the development of efficient methods for controlling polymer synthesis processes using heuristic optimization techniques. To solve the problem of determining optimal conditions for complex chemical-technological processes, a genetic algorithm is proposed. The key stages of its implementation are defined using modern software development tools. A kinetic modeling approach is presented for evaluating the primary molecular characteristics of polymer products, based on the use of statistical moments of the molecular weight distribution. The application of the genetic algorithm to this process enabled the identification of an optimal two-point control regime, facilitating the production of polymers with desired properties. Computational experiments demonstrated that variations in the mode of regulator feed in conditions of multi-point molecular weight control constitute a significant factor in managing complex processes. This approach provides a basis for planning the molecular parameters of polymer products in the context of continuous production systems.