Cold-Chain Resilience for Perishable Dairy: A Simulation-Based Sourcing, Inventory, and Location Decisions

Authors

DOI:

https://doi.org/10.65069/jessd21202618

Keywords:

Resilient Perishable Products Supply Chain, Cold Chain Logistics, Optimization, Simulation, Sustainability, Decision Support, Third-Party logistics (3PL)

Abstract

Perishable food cold chains face significant challenges arising from product perishability, temperature-control requirements, high logistics costs, and environmental concerns. The geographical dispersion of customers and the time and temperature requirements of dairy products make it challenging to determine appropriate distribution centre locations and coordinate sourcing and inventory decisions while simultaneously achieving cost efficiency, timely delivery, and reduced carbon emissions. This study aims to optimize the cold chain distribution network of Nada Company, a dairy producer in Riyadh, Saudi Arabia, serving customers in Oman. The study employs AnyLogistix, integrating Greenfield Analysis, Network Optimization, and simulation to determine suitable distribution centre locations, evaluate network performance, and support strategic distribution network decision-making. Greenfield Analysis initially identified three potential locations in Sohar, Salalah, and Samail, while Network Optimization determined that retaining two distribution centres in Sohar and Salalah provided a more efficient configuration. Compared with the Greenfield configuration, the optimized network reduced transportation costs from $2.13 million to $1.84 million and CO₂ emissions from 949,784 to 821,524, while maintaining the same total flow and demand fulfilment. The findings demonstrate that integrating network optimization and simulation can support more efficient and sustainable cold chain network design and evidence-based distribution decisions, providing a practical decision-support framework for perishable dairy products.

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Published

2026-08-24

How to Cite

Cold-Chain Resilience for Perishable Dairy: A Simulation-Based Sourcing, Inventory, and Location Decisions. (2026). Journal of Expert Systems and Sustainable Development, 2(1), 133-151. https://doi.org/10.65069/jessd21202618