Article Details

Abstract

In response to the problems of scattered customer distribution and electric vehicle range in logistics and distribution, this paper designs an electric logistics vehicle routing optimization algorithm to solve the Electric Vehicle Routing Problem (EVRP). Based on the problem of electric logistics vehicles, a model of the EVRPTW problem is established. Starting from the final distribution cost, the model solution with the lowest possible final cost is obtained under the constraints of electricity, load capacity, and customer time window. Based on the model of EVRPTW, it uses the Genetic Algorithm to randomly generate initial population, and ensures the complexity of the solution in the crossover, mutation, and other processes. Taking Jiaxing logistics routing planning as an example, the designed method is effective after practical verification.

Keywords

vehicle delivery; routing optimization; Evolutionary Algorithm; Genetic Algorithm

References

1. [1] LI Y，LIM M K，TAN Y S，et al. Sharing Economy to Improve Routing for Urban Logistics Distribution Using Electric Vehicles [J].Resources，Conservation and Recycling，2022，153：104585.
2. [2] Liu Yunzhong, Xuan Huiyu A Review of Models and Algorithms for Vehicle Routing Problems [J]. Journal of Management Engineering, 2005 (1): 124-130
3. [3] Cao Zhuo, Wang Xinxin, Xu Qian, etc Research on Optimization of Logistics Delivery Path for Electric Vehicles Based on the Internet of Vehicles [J]. Logistics Technology, 2023, 46 (15): 26-30
4. [4] Field Research on Optimization of Delivery Path for Pure Electric Refrigerated Trucks with Fuzzy Time Window [D]. Hangzhou: Zhejiang University of Technology, 2019
5. [5] WANG J，GAO T T，ZHANG J Z，et al. Research on Joint Distribution Path Planning of Electric Logistics Vehicles with Different Recharge Modes [J].Transportation Research Record，2024（4）：145-156.
6. [6] Lai Jinfang Research on the Distribution Path Planning of Electric Logistics Vehicles in Company A [D]. Xiamen: Xiamen University, 2022
7. [7] YANG S Y，NING L J，TONG L C，et al. Integrated Electric Logistics Vehicle Recharging Station Location-routing Problem with Mixed Backhauls and Recharging Strategies [J/OL].Transportation Research Part C: Emerging Technologies，2022，140：103695[2024-07-11].https://www.sciencedirect.com/science/article/abs/pii/S0968090X2200136X?via%3Dihub.
8. [8] Zhang Zhihao Research on Distribution Path Optimization of W Company Based on Electric Logistics Vehicles [D]. Jinan: Jinan University, 2023
9. [9] YE C，HE W J，CHEN H Q. Electric Vehicle Routing Models and Solution Algorithms in Logistics Distribution: A Systematic Review [J].Environmental Science and Pollution Research，2022，29：38：57067-57090.
10. [10] Promote oneself Research on Path Optimization Problem with Time Window Based on Electric Vehicles [D]. Dalian: Dalian Maritime University, 2015
11. [11] YU M X，LUO Q，WANG H B，et al. Electric Logistics Vehicle Path Planning Based on the Fusion of the Improved A-Star Algorithm and Dynamic Window Approach [J].World Electric Vehicle Journal，2023，14（8）：213-221.

Funding

Key Research Platform Project for Ordinary Universities in Guangdong Province (2024CYPT004); Characteristic Innovation Project of Ordinary Universities in Guangdong Province (2023KTSCX351); Research and Practice Project on Teaching Reform of Higher Vocational Education in Guangdong Province (2023JG511); Guangdong Provincial Education Science Planning Project (2023GXJK946)

About the authors

Yu Fahong (1977.11-), male, Han nationality, from Jianli, Hubei, professor, PhD, research direction: network security, intelligent computing; Corresponding author: Chen Meijia (September 1980-), female, Han ethnicity, from Wuxue, Hubei Province, lecturer, master's degree, research direction: vocational education, intelligent computing.