Architectural Model of the Adaptive Management Subsystem for Changes in the Duty Schedule under Specified Constraints

Viktor V. Korolenko, Svetlana V. Igrunova, Olga V. Sobenina and Elena V. Nesterova
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Viktor V. Korolenko: Voronezh State Technical University
Svetlana V. Igrunova: Voronezh State Technical University
Olga V. Sobenina: Voronezh State Technical University
Elena V. Nesterova: Belgorod State National Research University

Economics. Information Technologies, 2026, vol. 53, issue 2, 471-484

Abstract: The work addresses the problem of automating duty management processes in organisations with a complex hierarchical structure, including military educational institutions. The automated information system being developed will ensure a full cycle of duty management within the organisation. The system is built on the basis of a modular approach and includes seven interconnected components: modules for authentication and authorisation, administration, duty distribution and aggregation, assignment of duties to units, modification of the duty schedule, display of the current schedule, and statistics. Each module performs strictly defined functions, providing a comprehensive solution to the task. The article describes the results of modelling the component responsible for modifying the duty schedule. It also presents the results of developing functional requirements for the corresponding system module. The focus on the duty schedule modification module is justified by the high frequency of schedule adjustments. The developed system significantly optimises duty management processes, reduces the time required to generate schedules, and improves control efficiency. The research results can be used in the development of similar systems for other organisations whose activities involve planning and allocation of various tasks, works, and resources

Keywords: automation of processes; duty schedule; information system; module; calculation period; structure; requirements; function (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eul:ecoinf:v:53:y:2026:i:2:p:471-484

DOI: 10.52575/2687-0932-2026-53-2-471-484

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