Path optimization of multi-type vehicle mixed distribution

Juan Teng; Chuanxiang Ren; Xiaoqi Wang; Fangfang Fu; Fujiang Ding; Guangheng Zhou

doi:10.1117/12.2689588

7 September 2023 Path optimization of multi-type vehicle mixed distribution

Juan Teng, Chuanxiang Ren, Xiaoqi Wang, Fangfang Fu, Fujiang Ding, Guangheng Zhou

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127906F (2023) https://doi.org/10.1117/12.2689588
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

In order to study the path optimization problem of multi-type vehicle mixed distribution, a multi-type vehicle mixed distribution path optimization model is established in this paper and the genetic algorithm is used to solve the model. The mixed distribution of multi-type vehicle and the separate distribution of single type vehicle are simulated by an example. The simulation results show that, compared with the gasoline vehicles distributed separately, the mixed distribution of gasoline vehicles and electric vehicles can reduce the carbon emission by 26% and the total cost by 5.4%. Mixed distribution of gasoline and electric vehicles can reduce the total cost by 10% compared with the electric vehicles distributed separately. The research results of this paper can provide effective reference for logistics enterprises to reduce costs and promote the green development of logistics.

Citation Download Citation

Juan Teng, Chuanxiang Ren, Xiaoqi Wang, Fangfang Fu, Fujiang Ding, and Guangheng Zhou "Path optimization of multi-type vehicle mixed distribution", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127906F (7 September 2023); https://doi.org/10.1117/12.2689588

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