Development of a Hybrid Decision-Making Method Based on a Simulation-Genetic Algorithm in a Web-Oriented Metallurgical Enterprise Information System

The modern large industrial enterprises are faced with the problem of collecting, centralized storage and intellectual analysis of a large volume of production data with the goal of timely output of control actions, including in real time. The paper focuses on a web-oriented distributed metallurgical enterprise information system designed to support decision making with the help of data mining and simulation of multi-agent resource conversion processes. In order to support the optimization of production processes, a hybrid decision-making method based on a simulation-genetic algorithm is proposed. The hybrid method is implemented in the modeling subsystem of the metallurgical enterprise information system. The application of the method in solving the problem of the enterprise organizational processes optimization made it possible to develop concrete practical recommendations.