Application of Artificial Intelligence in Strategic Management at a Manufacturing Enterprise: Development of a Software Module for Multi-Criteria Optimization of Product Output

The article presents a study devoted to the development of a software module that optimizes the output of a mechanical engineering enterprise taking into account profit maximization. Two key criteria are considered: fulfillment of contractual obligations and maximization of sales revenue. An approach to solving a multi-criteria optimization problem using a genetic algorithm, which is one of the methods used in the field of artificial intelligence to solve complex optimization and search problems, is described. In the context of demand uncertainty caused by economic, social and political changes, the proposed solution is relevant for strategic management of the enterprise. It promotes flexible response to market changes, reduces the risks of underproduction or overproduction, and increases competitiveness. The development of such tools is of great importance for improving the efficiency of planning and management in mechanical engineering. An algorithm for calculating a multi-criteria problem is presented, implemented in the Java language, using the JavaFX library for the graphical interface and Apache POI for data export. The architecture of the software prototype is considered, incl. hierarchy of the program composition and ER - data model. The developed software prototype provides the ability to enter resource parameters, production volumes, and select optimization criteria. Experimental testing of the developed module was carried out on various scenarios for optimizing output, comparing the obtained solutions with the results of calculations in MS EXCEL, which confirmed the correctness of the algorithm used. The article emphasizes the importance of using modern optimization methods and software for developing intelligent information systems for managing a multi-criteria production plan for output.

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Publication Details

Journal
Intellekt Sist Proizv
Published
2025-10-08
DOI
https://doi.org/10.22213/2410-9304-2025-3-33-41
Primary Topic
Economic and Technological Systems Analysis
Type
article
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article

Application of Artificial Intelligence in Strategic Management at a Manufacturing Enterprise: Development of a Software Module for Multi-Criteria Optimization of Product Output

S. V. Vologdin, D. V. Tselischev, A. V. Demyshev
Intellekt Sist Proizv
Economic and Technological Systems Analysis
article

Application of Artificial Intelligence in Strategic Management at a Manufacturing Enterprise: Development of a Software Module for Multi-Criteria Optimization of Product Output

S. V. Vologdin, D. V. Tselischev, A. V. Demyshev
article en

Abstract

The article presents a study devoted to the development of a software module that optimizes the output of a mechanical engineering enterprise taking into account profit maximization. Two key criteria are considered: fulfillment of contractual obligations and maximization of sales revenue. An approach to solving a multi-criteria optimization problem using a genetic algorithm, which is one of the methods used in the field of artificial intelligence to solve complex optimization and search problems, is described. In the context of demand uncertainty caused by economic, social and political changes, the proposed solution is relevant for strategic management of the enterprise. It promotes flexible response to market changes, reduces the risks of underproduction or overproduction, and increases competitiveness. The development of such tools is of great importance for improving the efficiency of planning and management in mechanical engineering. An algorithm for calculating a multi-criteria problem is presented, implemented in the Java language, using the JavaFX library for the graphical interface and Apache POI for data export. The architecture of the software prototype is considered, incl. hierarchy of the program composition and ER - data model. The developed software prototype provides the ability to enter resource parameters, production volumes, and select optimization criteria. Experimental testing of the developed module was carried out on various scenarios for optimizing output, comparing the obtained solutions with the results of calculations in MS EXCEL, which confirmed the correctness of the algorithm used. The article emphasizes the importance of using modern optimization methods and software for developing intelligent information systems for managing a multi-criteria production plan for output.

Intellekt Sist ProizvVol. 23(3)
Izhevsk State Technical University (RU)
Openalex Percentile: Top 26%
Economic and Technological Systems Analysis
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