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Cost-based multi-parameter logistics routing path optimization algorithm

1 School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China
2 O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, USA
3 Control Technology Institute, Wuxi Institute of Technology, Wuxi, Jiangsu, China

The traditional path optimization problem is to consider the shortest path of the vehicle, but the shortest path does not effectively reduce the logistics cost. On the contrary, in the case of one-sided pursuit of the shortest path, it may cause some negative effects. This paper constructs a more realistic path optimization model on the path of traditional logistics distribution, and designs a path model based on simulated annealing algorithm which taking fuel consumption, cost, road gradient and condition of vehicle into account. The algorithm model of load capacity and other problems is used to verify the algorithm of the model through a simulation case of multiple distribution points. The experimental results show that the path optimization strategy considering the gradient of the road reduces the cost of the vehicle path, indicating the correctness of considering the vehicle load and road gradient factors in logistics transportation.
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Keywords path optimization; simulated annealing; fuel consumption analysis; cost optimization; road condition analysis

Citation: Fulin Dang, Chunxue Wu, Yan Wu, Rui Li, Sheng Zhang, Huang Jiaying, Zhigang Liu. Cost-based multi-parameter logistics routing path optimization algorithm. Mathematical Biosciences and Engineering, 2019, 16(6): 6975-6989. doi: 10.3934/mbe.2019350

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