Optimization of consumer order fulfillment management in a digitalized organizational system of interaction with producers

The article explores the application of an optimization approach in managerial decision-making within a digitalized organizational system for consumer order fulfillment. It is demonstrated that when constructing a model of interaction between consumers and producers, the characteristics of human-machine environment elements must be taken into account. Such consideration enables the optimization of management in the interaction between ergatic and non-ergatic elements based on performance, reliability, and cost indicators. The formation of the optimization model is based on the introduction of alternative variables characterizing the choice of the number of ergatic elements interacting with a specific non-ergatic element. The extremal requirement considered is the maximization of the performance of the consumer order fulfillment process in the digitalized organizational system, while the boundary requirements are the specified levels of reliability and costs. A transition to an equivalent unconstrained optimization function is implemented. The algorithmic procedure for managerial decision-making is oriented towards the structure of the equivalent optimization function and includes several stages: automatic generation of feasible solutions in a randomized environment, iterative settings of variables, verification of the stopping condition for the iterative process, and expert selection of the final solution.

1. Glushchenko V. Scientific theory of technological structures and research directions of its practical application. Bulletin of Science and Practice. 2020;6(4):488–504. (In Russ.).

2. Weill P., Woerner S. What's Your Digital Business Model?: Six Questions to Help You Build the Next-Generation Enterprise. Moscow: Alpina Publisher; 2019. 264 p. (In Russ.).

3. 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

4. Mrochkovsky N.S., Lyandau Yu.V., Pushkin I.S., Krivonogov E.A. Main tendencies of digital transformation of business. Ekonomika i predprinimatel'stvo. 2019;(4):89–91. (In Russ.).

5. Ryndin N.A. Algorithmization of the multivariate structuring process in digitalized organizational systems. Modeling, Optimization and Information Technology. 2023;11(1). (In Russ.). https://doi.org/10.26102/2310-6018/2023.40.1.005

6. Lvovich Ya.E., Pupykin A.N. Intellectualization of management in organizational systems with a digital hub of performance results based on optimization modeling. Modeling, Optimization and Information Technology. 2024;12(2). (In Russ.). https://doi.org/10.26102/2310-6018/2024.45.2.018

7. Selezneva M.P. Electronic auctions in the conditions of digital transformation. Journal of Economy and Business. 2021;(11-1):197–199. (In Russ.). https://doi.org/10.24412/2411-0450-2021-11-1-197-199

8. Yermolova V.V., Lvovich Ya.E., Preobrazhenskiy Yu.P. Optimizing interaction of the components in a human-machine system of digitalization. Modeling, Optimization and Information Technology. 2023;11(2). (In Russ.). https://doi.org/10.26102/2310-6018/2023.41.2.031

9. L'vovich I.Ya., L'vovich Ya.E., Frolov V.N. Informatsionnye tekhnologii modelirovaniya i optimizatsii. Kratkaya teoriya i prilozheniya. Voronezh: Publishing and Printing Center Nauchnaya kniga; 2016. 444 p. (In Russ.).

10. Sobol' I.M. Chislennye metody Monte-Karlo. Moscow: Nauka; 1973. 312 p. (In Russ.).

11. L'vovich I.Ya. Prinyatie reshenii na osnove optimizatsionnykh modelei i ekspertnoi informatsii. Voronezh: Publishing and Printing Center Nauchnaya kniga; 2023. 232 p. (In Russ.).