Utilizing Cloud Computing for Research and Optimization of Complex Physicochemical Processes

The paper presents the main stages of the software implementation of heuristic methods for solving optimization problems based on a mathematical model of chemical reaction kinetics. In the context of digital transformation in manufacturing and the Industry 4.0 concept, a key direction is the integration of cloud and high-performance computing into research processes. This enables the creation of digital tools that ensure highly efficient modeling of complex physicochemical systems. To optimize such complex systems, heuristic methods are chosen, grounded in principles of stochastic search and global optimization, which facilitate effective exploration of the solution space. The software implementation of several heuristic methods is integrated into the computational core of a developed cloud-based SaaS service, designed for comprehensive research and modeling of complex physicochemical systems. The computational tasks are run in a remote environment using Docker containerization technology, ensuring scalability and convenience in distributed data processing. The functionality of the created system is demonstrated through the study of the Michaelis-Menten enzymatic reaction kinetics-a classical model of biochemical kinetics widely used in scientific research.