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Optimisation of agricultural logistics: A systematic review of modelling techniques and economic potentials

2026/04/14 by Nikolas Bublik, Sebastian Heß · 1 voice
Agricultural and Biological Sciences · Engineering · #Food Supply Chain Traceability #Optimization and Mathematical Programming #Vehicle Routing Optimization Methods

paper · doi:10.17221/76/2025-agricecon

openalex publication_date 2026/04/14 · openalex created_date 2026/04/15 · openalex updated_date 2026/07/14

Abstract

Agricultural logistics face unique challenges such as seasonal demand fluctuations, perishability, and geographic dispersion. The paper systematically analyses 63 peer-reviewed articles from 2013 to 2025, focusing on key optimisation techniques, including multi-criteria decision-making (MCDM), vehicle routing problems (VRP), and path planning problems (PPP). The findings highlight how logistics optimisation can reduce operational costs, improve resource utilisation, and enhance supply chain resilience. Additionally, the study identifies gaps in inbound logistics research and emphasises the need for further integration of digital technologies. Future research should focus on comprehensive, technology-driven solutions to improve adaptability and transparency in agricultural supply chains. Key findings reveal that optimised logistics models can lead to cost reductions of up to 58%, emissions savings of over 60%, and significant improvements in delivery time, field efficiency, and customer satisfaction.

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