TY - JOUR
T1 - Optimal electric vehicle routing for minimizing electrical energy consumption based on hybrid genetic algorithm
AU - Chen, Hong
AU - Murata, Tomohiro
N1 - Publisher Copyright:
© 2019 Turkiye Klinikleri Journal of Medical Sciences. All rights reserved.
PY - 2019
Y1 - 2019
N2 - — This paper presents a novelty model for solving a routing problem for delivery service using EV trucks called electric vehicle routing problem (EVRP). We also present a meta-heuristic algorithm by combining genetic algorithm and Tabu Search algorithm, to solve the EVRP. The difficulty of using a EV truck for a good delivery service is finding out an optimal route in a huge number of rotes. additionally, it also need to consider the short driving distance problem because of battery limited of EV. The formulation present was based on a mixed integer programming formulation, objective to minimum the total electrical consumption and multiple constraints, which considered the electric recovery in a gradient road and arrange the loading assignment, to improve the electrical consumption efficiency. additionally, the electrical consumption balance of every trucks was considered. It good to reduce the charging operation time and improve the operations efficiency for this problem. We designed and executed five experiments to evaluate our formulation and algorithm, verified the effectiveness of our idea in EVRP problem. Experiments show that, the total electrical consumption calculated by proposed EVRP model could be improved 2.3% than a conventional VRP model, and the operations time balance objective made 48.3%’s reducing of charging operation time.
AB - — This paper presents a novelty model for solving a routing problem for delivery service using EV trucks called electric vehicle routing problem (EVRP). We also present a meta-heuristic algorithm by combining genetic algorithm and Tabu Search algorithm, to solve the EVRP. The difficulty of using a EV truck for a good delivery service is finding out an optimal route in a huge number of rotes. additionally, it also need to consider the short driving distance problem because of battery limited of EV. The formulation present was based on a mixed integer programming formulation, objective to minimum the total electrical consumption and multiple constraints, which considered the electric recovery in a gradient road and arrange the loading assignment, to improve the electrical consumption efficiency. additionally, the electrical consumption balance of every trucks was considered. It good to reduce the charging operation time and improve the operations efficiency for this problem. We designed and executed five experiments to evaluate our formulation and algorithm, verified the effectiveness of our idea in EVRP problem. Experiments show that, the total electrical consumption calculated by proposed EVRP model could be improved 2.3% than a conventional VRP model, and the operations time balance objective made 48.3%’s reducing of charging operation time.
KW - Genetic algorithm
KW - Index electric vehicle routing problem
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=85065784451&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065784451&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85065784451
SN - 2078-0958
VL - 2239
SP - 526
EP - 531
JO - Lecture Notes in Engineering and Computer Science
JF - Lecture Notes in Engineering and Computer Science
T2 - 2019 International MultiConference of Engineers and Computer Scientists, IMECS 2019
Y2 - 13 March 2019 through 15 March 2019
ER -