Optimizing Cold Chain Distribution Routes Considering Dynamic Demand: A Low-Emission Perspective

Xiaoyun Jiang (), Xiangxin Liu, Fubin Pan and Zinuo Han
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Xiaoyun Jiang: School of Economics and Management, Xiamen University of Technology, Xiamen 361024, China
Xiangxin Liu: School of Economics and Management, Xiamen University of Technology, Xiamen 361024, China
Fubin Pan: School of Economics and Management, Xiamen University of Technology, Xiamen 361024, China
Zinuo Han: School of Economics and Management, Xiamen University of Technology, Xiamen 361024, China

Sustainability, 2024, vol. 16, issue 5, 1-17

Abstract: Cold chain logistics, with its high carbon emissions and energy consumption, contradicts the current advocacy for a “low-carbon economy”. Additionally, in the real delivery process, customers often generate dynamic demand, which has the characteristic of being sudden. Therefore, to help cold chain distribution companies achieve energy-saving and emission-reduction goals while also being able to respond quickly to customer needs, this article starts from a low-carbon perspective and constructs a two-stage vehicle distribution route optimization model that minimizes transportation costs and refrigeration costs, alongside carbon emissions costs. This research serves to minimize the above-mentioned costs while also ensuring a quick response to customer demands and achieving the goals of energy conservation and emission reduction. During the static stage, in order to determine the vehicle distribution scheme, an enhanced genetic algorithm is adopted. During the dynamic optimization stage, a strategy of updating key time points is employed to address the dynamic demand from customers. By comparing the dynamic optimization strategy with the strategy of dispatching additional vehicles, it is demonstrated that the presented model is capable of achieving an overall cost reduction of approximately 17.13%. Notably, carbon emission costs can be reduced by around 17.11%. This demonstrates that the dynamic optimization strategy effectively reduces the usage of distribution vehicles and lowers distribution costs.

Keywords: cold chain distribution; dynamic demand; low carbon; path optimization; genetic algorithms (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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