With the development of social economy, the demand for fresh food is increasing. The cold chain logistics has become a crucial way to transport fresh food. However, the cold chain logistics in China is not sufficient to meet market demand. To reduce logistics costs and optimize distribution efficiency, a dynamic path planning model for cold chain logistics distribution vehicles on the basis of an improved IAFS is designed. Firstly, considering the shortcomings of traditional IAFS such as poor convergence and susceptibility to local optima, the traditional method is optimized. Secondly, considering the coordination of various delivery links and minimizing transportation costs, a cold chain logistics distribution model is built under the dynamic path planning scheme. From the results, the optimal values of the improved algorithm were 0.0142, 0.0122 and 0.0675 in the solution process of Beale, Levy and Rastrigin functions, respectively, which were closer to the target optimal value and had better performance than the other three comparative algorithms. The dynamic path planning model for cold chain logistics vehicles based on this algorithm improved the space utilization of distribution vehicles by 1%- 11% under static demand and dynamic demand, and reduced the distribution time and distance travelled by 0.15 h and 0.39 km, respectively. The study optimizes the dynamic path planning for cold chain logistics transportation vehicles by introducing improved algorithms, which can be applied to practical situations while reducing costs and improving efficiency, providing reference for other logistics distribution research.
Dynamic Path Planning Model for Cold Chain Logistics Delivery Vehicles Based on Improved Artificial Fish Swarm Algorithm
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 23 , 2 ; 869-881
2025-08-01
13 pages
Article (Journal)
Electronic Resource
English
Dynamic demand , Logistics distribution , Cold chain logistics , AFSA , Path planning Electrical Engineering , Automotive Engineering , Engineering , Civil Engineering , User Interfaces and Human Computer Interaction , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics
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