The article examines the characterization of an organizational system with alternative supplies and its management process at the level of structural modeling. It is shown that the formation of structural models is a preliminary stage for optimization modeling, which provides algorithmization of intellectual support for decision-making by the control center. It is determined that for further use in optimization modeling, the structuring of the functioning of an organizational system with alternative supplies should include a description of the characteristics of connections when interacting between the control center and organization objects. It is substantiated that these characteristics should include numerical sets of objects, suppliers, supply costs, and indicators characterizing the effectiveness of deliveries. The purposefulness of achieving certain results of activity is established by the requirements of the control center to integral costs and deadlines for each object. It is assessed that direct transformation of the structural model of the functioning of the studied system into a management structure based on expert-optimization decisions does not allow choosing the best option for supplies in most cases. In this case, the traditional management process should be supplemented with a subsystem of intellectual support for managerial decisions. Intellectualization is proposed to be carried out through sequential solution of several optimization problems followed by transformation of optimization results into final managerial decision ensuring coordination of expert and formalized assessments. This sequence aims at gradual reduction of multi-alternative optimization tasks starting from forming a reduced set transitioning to dominant variants' set and finally moving optimizable variables from alternatives to parameters. The feasibility of transitioning to parametric optimization based on machine learning dependencies of efficiency indicators from parameters using retrospective data for objects similar to the current state of the organizational system with alternative supplies is considered.
1. Weill P., Woerner S. What's Your Digital Business Model?: Six Questions to Help You Build the Next-Generation Enterprise. Moscow: Alpina Publisher; 2019. 257 p. (In Russ.).
2. Korchagin S.G., Ryndin A.A., Ryndin N.A. Upravlenie v organizatsionnykh sistemakh na osnove tsifrovykh tekhnologii. Voronezh: Nauchnaya kniga; 2025. 248 p. (In Russ.).
3. Sokol'nikov V.V. Operational management of construction processes and the resources procurement in the construction and installation company. Bulletin of Civil Engineers. 2017;(1):147–152. (In Russ.).
4. Kolchedantsev L.M., Sokolnikov V.V. Substantiation of Platform of Automation of Operative Planning and Management System of Construction Company. Housing Construction. 2015;(4):38–42. (In Russ.).
5. Gretchenko A.I., Gorokhova I.V. Digital Platform: A New Business Model in the Russian Economy. Vestnik of the Plekhanov Russian University of Economics. 2019;(1):62–72. (In Russ.). https://doi.org/10.21686/2413-2829-2019-1-62-72
6. L'vovich Ya.E., L'vovich I.Ya., Choporov O.N., et al. Optimizatsiya tsifrovogo upravleniya v organizatsionnykh sistemakh. Voronezh: Nauchnaya kniga; 2021. 191 p. (In Russ.).
7. L'vovich I.Ya. Prinyatie reshenii na osnove optimizatsionnykh modelei i ekspertnoi informatsii. Voronezh: Nauchnaya kniga; 2023. 232 p. (In Russ.).
8. Novosel'tsev V.I. Sistemnyi analiz: sovremennye kontseptsii. Voronezh: Izdatel'stvo "Kvarta"; 2003. 360 p. (In Russ.).
9. Nechiporenko V.I. Strukturnyi analiz sistem (effektivnost' i nadezhnost'). Moscow: Sovetskoe radio; 1977. 216 p. (In Russ.).
10. Trakhtengerts E.A. Komp'yuternaya podderzhka prinyatiya soglasovannykh gruppovykh reshenii. Moscow: Novye tekhnologii: Mashinostroenie; 2002. 24 p. (In Russ.).
11. Lvovich Ya.E., Shevyreva E.A. Optimization of management in an organizational system with alternative supplies based on a multivariate choice model and algorithm. Modeling, Optimization and Information Technology. 2024;12(4). (In Russ.). https://doi.org/10.26102/2310-6018/2024.47.4.018
12. Donskoy V.I. Extraction of optimization models from data: an application of neural networks. Tavricheskii vestnik informatiki i matematiki. 2018;(2):71–89. (In Russ.).
Shevyreva Elena Alexandrovna
Voronezh Institute of High Technologies
Voronezh, Russian Federation
