Keywords: organizational system, management, expert evaluation, territorial distribution, optimization, multi-method approach
Optimization of management in an organizational system with territorial distribution of the results of the activities of objects
UDC 681.3
DOI: 10.26102/2310-6018/2025.51.4.057
This article explores the use of an expert-optimization approach to improve management efficiency in organizational systems with geographically dispersed outcomes. The core management mechanism involves the central authority allocating integrated resources among objects within a specific operational timeframe. The study identifies key factors that influence resource allocation priorities to achieve targeted outcomes for these objects. A method is proposed to derive quantitative priority coefficients, based on ranking each component and calculating an additive combination of their values. This method integrates multiple approaches, combining group expert evaluations of priority rules based on temporal characteristics of numerical rankings with individual expertise to determine weighting factors using logical ordering techniques. The article presents the results of logically ordering components that characterize the diverse environments of objects, focusing on resource allocation to meet planned volume within set deadlines. The study emphasizes the importance of using priority coefficient evaluations for optimizing the selection of objects to receive allocated resources. A multi-option optimization model is developed to select objects with the highest priority while satisfying balance constraints. To implement this multi-method approach, numerical optimization is recommended using various search algorithms. Additionally, a group expert evaluation process, led by a primary expert, is proposed to finalize decisions on managing integrated resource allocation in organizational systems with geographically distributed outcomes.
1. Novikov D.A. Teoriya upravleniya organizatsionnymi sistemami. Moscow: LENAND; 2022. 500 p. (In Russ.).
2. 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.).
3. Sokol'nikov V.V. Modelirovanie obespecheniya kachestva stroitel'no-montazhnykh rabot i organizatsionnogo razvitiya stroitel'nogo predpriyatiya. Housing Construction. 2013;(5):47–50. (In Russ.).
4. Tsopa N.V., Khalilov A.E. Resource Support of Investment and Construction Projects. Ekonomika stroitel'stva i prirodopol'zovaniya. 2022;(1-2):23–30. (In Russ.).
5. Barkalov S.A., Burkova I.V., Kolpachev V.N., Potapenko A.M. Modeli i metody raspredeleniya resursov v upravlenii proektami. Moscow: V.A. Trapeznikov Institute of Control Sciences of RAS; 2004. 85 p. (In Russ.).
6. 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.).
7. 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.).
8. Litvak B.G. Ekspertnye otsenki i prinyatie reshenii. Moscow: Patent; 1996. 271 p. (In Russ.).
9. L'vovich I.Ya. Prinyatie reshenii na osnove optimizatsionnykh modelei i ekspertnoi informatsii. Voronezh: Nauchnaya kniga; 2023. 231 p. (In Russ.).
10. Yudin D.B., Yudin A.D. Ekstremal'nye modeli v ekonomike. Moscow: Ekonomika; 1979. 288 p. (In Russ.).
11. L'vovich Ya.E. Mnogoal'ternativnaya optimizatsiya: teoriya i prilozheniya. Voronezh: Kvarta; 2006. 415 p. (In Russ.).
12. Karpenko A.P. Analiz i sintez populyatsionnykh algoritmov global'noi optimizatsii. T.1. Moscow: Izd-vo MGTU im. N.E. Baumana; 2024. 368 p. (In Russ.).
Keywords: organizational system, management, expert evaluation, territorial distribution, optimization, multi-method approach
For citation: Boklashov I.I., Ivanov D.V., Yakov L.E. Optimization of management in an organizational system with territorial distribution of the results of the activities of objects. Modeling, Optimization and Information Technology. 2025;13(4). URL: https://moitvivt.ru/ru/journal/pdf?id=2093 DOI: 10.26102/2310-6018/2025.51.4.057 (In Russ).
Received 06.10.2025
Revised 12.12.2025
Accepted 18.12.2025