Optimization modeling of personnel management process with automated devices in the information system of customer order fulfillment

The paper proposes an optimization approach to managing the interaction of personnel with automated devices in the information environment of a digitalized organizational system of customer order fulfillment using the results of simulation modeling. To build a simulation model of mass service system, the interaction of personnel with automated devices is considered as the interaction of non-ergatic and ergatic elements in the human-machine environment. The logical scheme of transforming the flow of consumer requests through local aggregators and service channels, including non-ergatic and ergatic elements, when transferring digital data on the order to manufacturers for their material realization is substantiated. It is proposed to vary the intensity of service not by choosing the parallel channels involved, but directly by the value of the total intensity, depending on the number of non-ergotic and ergatic elements. Formation of the optimization model is carried out, the optimizable variables of which are the values of intensities. The requirement of maximizing the system performance is considered as an extreme requirement, and the requirements of providing an acceptable level of costs and probability of erroneous actions act as boundary requirements. Transitions from the optimization problem with constraints to the equivalent optimization problem without constraints are carried out. Algorithmization of managerial decision making on choosing the number of interacting non-ergotic and ergatic elements by building an iterative search process using an optimization model in the process of simulation modeling of a digitalized organizational system of customer order fulfillment is proposed.

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. 264 p. (In Russ.).

2. 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

3. 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

4. Shaidakov I.E. Automation of Processes and Introduction of Remote Customer Service – Key Trends of the Service Companies' Development. Izvestiya Sankt-Peterburgskogo gocudarstvennogo ekonomicheskogo universiteta. 2016;(5):169–172. (In Russ.).

5. Bakulin A.Yu., Lvovich Ya.E. Analysis and Optimization of Organizational System Functioning Efficiency with Automated Service Devices on the Basis of Simulation Modeling. Modeling, Optimization and Information Technology. 2024;12(2). (In Russ.). https://doi.org/10.26102/2310-6018/2024.45.2.030

6. 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

7. Snapelev Yu.M., Starosel'skii V.A. Modelirovanie i upravlenie v slozhnykh sistemakh. Moscow: Sovetskoe radio; 1974. 264 p. (In Russ.).

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: Nauchnaya kniga; 2016. 444 p. (In Russ.).

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