Journal of System Simulation
Abstract
Abstract: As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization, this paper builds a path optimization model to minimize the comprehensive distribution cost. The model combines with the characteristics of fresh distribution, and comprehensively considers the transportation cost, carbon emission, refrigeration, cargo damage and time window constraints during cold chain transportation. Then, an improved ant colony algorithm is designed to solve this model. At the initial stage, the genetic algorithm is adopted to generate the initial pheromone, and then the ant colony algorithm is applied to conduct the subsequent optimization search. The Metropolis criterion of the simulated annealing algorithm is introduced to screen the high-quality solution. Finally, the effectiveness of the proposed optimization model and improved algorithm is verified by several experiments. The proposed model and improved algorithm have a certain significance for the research on the optimization of the cold chain distribution route of fresh food under the concept of low-carbon sustainable development. They helps the cold chain transportation industry to transition to low-carbon economy.
Recommended Citation
Bao, Huifang; Fang, Jie; Zhang, Jinsi; and Wang, Chuansheng
(2024)
"Optimization on Cold Chain Distribution Routes Considering Carbon Emissions Based on Improved Ant Colony Algorithm,"
Journal of System Simulation: Vol. 36:
Iss.
1, Article 14.
DOI: 10.16182/j.issn1004731x.joss.22-0963
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss1/14
First Page
183
Last Page
194
CLC
TP301
Recommended Citation
Bao Huifang, Fang Jie, Zhang Jinsi, et al. Optimization on Cold Chain Distribution Routes Considering Carbon Emissions Based on Improved Ant Colony Algorithm[J]. Journal of System Simulation, 2024, 36(1): 183-194.
DOI
10.16182/j.issn1004731x.joss.22-0963
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