Work

Preparation of Big Data Sets for Optimization of Intercity Freight Driver Schedules

Year: 2026

Type: article

Abstract: The problem of using big data for optimal planning of work and rest of truck drivers in intercity freight transportation is considered. The problem is solved for a team of drivers in compliance with the EU regulation 561/2006. The proposed data preparation can reduce the practical computational complexity and find the optimal driver work schedule. The clustering of the initial data was substantiated for optimizing schedules based on the criterion of compatibility of transport orders. The compatibility of orders follows from the analysis of similarity of two consecutive transportation processes performed by one driver during his/her work shift. Simulation modelling was performed. The influence of the scale of the territory on the quality of the prepared initial data was also investigated. A rational range of the compatibility coefficient for the high-quality preparation of a large data set was substantiated.

Source: Communications - Scientific letters of the University of Zilina

DOI: 10.26552/com.c.2026.022

Authors: Olexandr Melnychenko, Myroslav Oliskevych, Nazar Khomyn, Olexandr Melnychenko, Myroslav Oliskevych, Nazar Khomyn

Institutions: National Transport University, Stepan Gzhytskyi National University of Veterinary Medicine and Biotechnologies Lviv

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: diamond

OpenAlex ID: W7154457270

FWCI:

Cites: 24

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