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Academic Journal of Computing & Information Science, 2023, 6(4); doi: 10.25236/AJCIS.2023.060413.

Cold Chain Distribution Route Optimization Considering Customer Satisfaction in the Context of Carbon Emission Reduction


Yiming Liu

Corresponding Author:
Yiming Liu

School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang, 050043, China


In view of the current situation of high energy consumption, high carbon emission, and in-creasingly demanding customer requirements for distribution services in cold chain logistics, this paper integrates carbon emission, time, and quality satisfaction factors to construct a path optimiza-tion model with the objectives of minimizing cold chain logistics costs and maximizing customer sat-isfaction, then converts the dual purpose into a single objective model through standardization and linear weighting method. In order to solve the model, it designs an improved genetic algorithm. The model and algorithm are tested using standard Solomon's algorithm, and the results are stable and accurate, which not only proves the effectiveness of the algorithm, but also shows that the model can reduce the cost of cold chain logistics to a low level while ensuring high customer satisfaction.


cold chain logistics, carbon emissions, customer satisfaction, genetic algorithm

Cite This Paper

Yiming Liu. Cold Chain Distribution Route Optimization Considering Customer Satisfaction in the Context of Carbon Emission Reduction. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 4: 97-105. https://doi.org/10.25236/AJCIS.2023.060413.


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