TY - JOUR
T1 - The Mathematical Model and an Genetic Algorithm for the Two-Echelon Electric Vehicle Routing Problem
AU - Zhang, Yue
AU - Zhou, Shenghan
AU - Ji, Xinpeng
AU - Chen, Bang
AU - Liu, Houxiang
AU - Xiao, Yiyong
AU - Chang, Wenbing
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2021/2/24
Y1 - 2021/2/24
N2 - In order to cope with the challenges of high cargo load and high timeliness distribution in logistics industry, as well as to alleviate the current situation of oil resource depletion and air pollution, this study established a mathematical model of two-echelon electric vehicle routing problem (2E-EVRP) and design a heuristic algorithm. The 2E-EVRP can be divided into the multiple depot vehicle routing problem (MDEVRP) and the split delivery vehicle routing problem (SDVRP). The proposed genetic algorithm is used to solve the MDEVRP, and the actual case of a logistics company in Beijing is taken as the calculation experiment, so as to verify the feasibility of the proposed algorithm and provide decision-making reference for the development of logistics enterprises. The results show that the total path length obtained by the proposed algorithm is optimized by 20.82 kilometers compared with the traditional simulated annealing algorithm.
AB - In order to cope with the challenges of high cargo load and high timeliness distribution in logistics industry, as well as to alleviate the current situation of oil resource depletion and air pollution, this study established a mathematical model of two-echelon electric vehicle routing problem (2E-EVRP) and design a heuristic algorithm. The 2E-EVRP can be divided into the multiple depot vehicle routing problem (MDEVRP) and the split delivery vehicle routing problem (SDVRP). The proposed genetic algorithm is used to solve the MDEVRP, and the actual case of a logistics company in Beijing is taken as the calculation experiment, so as to verify the feasibility of the proposed algorithm and provide decision-making reference for the development of logistics enterprises. The results show that the total path length obtained by the proposed algorithm is optimized by 20.82 kilometers compared with the traditional simulated annealing algorithm.
KW - Genetic algorithm
KW - Transportation
KW - Two-echelon electric vehicle routing
UR - https://www.scopus.com/pages/publications/85103133514
U2 - 10.1088/1742-6596/1813/1/012006
DO - 10.1088/1742-6596/1813/1/012006
M3 - 会议文章
AN - SCOPUS:85103133514
SN - 1742-6588
VL - 1813
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012006
T2 - 2020 International Conference on Modeling, Big Data Analytics and Simulation, MBDAS 2020
Y2 - 20 December 2020 through 21 December 2020
ER -