Data-Driven Modeling and Simulation in Forestry and Agricultural Product Transportation Management by Small Businesses: A Case Study

Galina Merkurjeva (), Vitalijs Bolsakovs, Jurijs Merkurjevs, Andrejs Romanovs and Wouter Faes
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Galina Merkurjeva: Institute of Information Technology, Riga Technical University, Kipsalas Street 6A, LV-1048 Riga, Latvia
Vitalijs Bolsakovs: Institute of Information Technology, Riga Technical University, Kipsalas Street 6A, LV-1048 Riga, Latvia
Jurijs Merkurjevs: Institute of Information Technology, Riga Technical University, Kipsalas Street 6A, LV-1048 Riga, Latvia
Andrejs Romanovs: Institute of Information Technology, Riga Technical University, Kipsalas Street 6A, LV-1048 Riga, Latvia
Wouter Faes: F.A.E.S. Consulting BV, Frankrijklei 86 A, B-2018 Antwerp, Belgium

Data, 2025, vol. 10, issue 7, 1-20

Abstract: This article proposes an innovative methodology for data-driven modeling and simulation of transportation management through cross-sectoral collaboration in small businesses. The present research is multidisciplinary and interdisciplinary in nature. We investigate the improvements in logistics management that can be achieved through cross-sector collaboration in agriculture and forestry. A data-driven method, such as symbolic regression, is used to identify the relationships between factors in a modeled system using mathematical expressions. These expressions are directly integrated into the simulation models. Simulation spreads the modeling of transportation processes over a period of time. The system dynamics model is designed to analyze and assess the performance of a system based on its past behavior and is, therefore, deterministic. The discrete-event model enables the simulation of future scenarios and outcomes over time, given random input variables. As new data become available, relationships within the symbolic regression method are discovered more accurately, and simulations are updated accordingly. The tools offered for implementation are supplemented by a multi-user web simulation. The proposed case study is based on a real-life example. The obtained results allow small agricultural companies to use transportation and labor resources more efficiently when organizing the transportation of their agricultural and forestry products. Integrating data-driven models into simulations enables a better interpretation of data across the entire data value chain.

Keywords: data-driven simulation; symbolic regression; transportation; cross-sector collaboration (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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