Development of a hierarchical transportation planning model with local segmentation of orders and adaptive vehicle selection
DOI:
https://doi.org/10.15587/1729-4061.2026.351416Keywords:
hierarchical transportation planning, order segmentation, vehicle selectionAbstract
The processes to plan transport deliveries in logistics systems involving hierarchical models have been investigated in this paper. The task to optimally plan freight delivery for transport and distribution logistics enterprises is associated with problems arising from fluctuations in demand, geographically distributed orders, as well as limited and heterogeneous resources.
The results of this study include the construction of a hierarchical model that allows for multi-level transportation planning, clustering of previously unclassified orders, and adjusting the choice of vehicles based on current conditions. Such adaptive choice of vehicles flexibly takes into account logistical constraints.
The findings indicate a reduction in transportation costs by 11.7% (p < 0.05). At the same time, it was found that under conditions of small samples, the stability of cluster solutions is limited and, therefore, additional verification and extended validation are required for their practical implementation.
The novelty of the proposed model is in the application of hierarchical decomposition of the multi-index transportation planning problem with the allocation of the global stage of cluster formation and the local stage of route planning. An approach to order clustering based on a limited sample of the closest applications in time and distance and an algorithm for adaptive selection of vehicles taking into account cost, carrying capacity and urgency of execution have been proposed.
The model built makes it possible to reduce the computational complexity of the problem compared to classical routing models while maintaining the interpretability of solutions at each stage due to transparent clustering rules. The scope of practical use of the results covers transport and logistics companies, delivery services, urban distribution systems, and retail logistics.
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Copyright (c) 2026 Ilona Drach, Oksana Kucheruk, Tetiana Kysil, Oleksandr Dykha, Serhii Matiukh

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