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  4. 2026
  5. VOL 48, NO 1 (2026)
  6. pp. 106-123

APPROACH TO SOLVING THE PROBLEM OF RESOURCE ALLOCATION IN THE IMPLEMENTATION OF CRITICAL LOGISTICS SCENARIOS

S.Yu. Skrupskyi, M.Yu. Tiahunova, O.V. Borovyk

Èlektron. model. 2026, 48(1):106-122

https://doi.org/10.15407/emodel.48.01.106

ABSTRACT

In todayʼs environment, critical scenarios that are carried out without constant logistical support and require effective resource management are becoming increasingly important in terms of security. Such missions include military operations of small mobile units, rescue missions in hard-to-reach areas, humanitarian expeditions in disaster or combat zones, environmental or scientific research in Arctic, mountainous, or desert regions, as well as long-term expeditions far from supply bases. One of the key aspects of planning such missions is resource provision, since it is the rational distribution of resources that largely determines the autonomy, endurance, and safety of participants. In the field, each participant must carry their own supply of resources or a portion of the total volume, which requires proper balancing of weight and volume. Inefficient distribution can lead to overloading of individual participants or a shortage of resources at critical moments of the mission. Therefore, the optimization task of efficient resource distribution among participants of autonomous groups, taking into account time, physical, and organizational constraints, becomes relevant. To formalize this, a mathematical model has been proposed that generalizes the classic Multiple Knapsack Problem (MKP), extended by the conditions of monotonic load reduction, fixed allocation of resources to a specific participant and day of resource use, as well as taking into account individual physical capabilities. A computer model developed on this basis, designed to be implemented in the form of a mobile application, enables the automation of the process of planning and distributing resources among participants in autonomous missions in accordance with their capabilities and specified constraints.

KEYWORDS

efficient resource allocation, knapsack problem, multiple knapsack problem, monotonic weight decrease, mathematical modeling.

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