Bi-objective collaborative electric vehicle routing problem: mathematical modeling and matheuristic approach

2022 ◽  
Author(s):  
Behdin Vahedi-Nouri ◽  
Hamidreza Arbabi ◽  
Fariborz Jolai ◽  
Reza Tavakkoli-Moghaddam ◽  
Ali Bozorgi-Amiri
Keyword(s):  
Mathematical Modeling ◽  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Routing Problem

scholarly journals Electric Vehicle Routing Problem with Industry Constraints: Trends and Insights for Future Research

2014 ◽  
Vol 3 ◽  
pp. 452-459 ◽  
Author(s):  
Anagnostopoulou Afroditi ◽  
Maria Boile ◽  
Sotirios Theofanis ◽  
Eleftherios Sdoukopoulos ◽  
Dimitrios Margaritis
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Future Research ◽  
Routing Problem

Recharge strategies for the electric vehicle routing problem with soft time windows and fast chargers

2021 ◽  
Vol 15 (4/5) ◽  
pp. 444
Author(s):  
Zhenping Li ◽  
Guohua Wu ◽  
Ke Zhang ◽  
Shuxuan Li ◽  
Chenglin Xiao ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Routing Problem ◽  
Soft Time Windows

scholarly journals Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions

2020 ◽  
Vol 12 (24) ◽  
pp. 10537
Author(s):  
Jin Li ◽  
Feng Wang ◽  
Yu He
Keyword(s):  
Energy Consumption ◽  
Vehicle Routing ◽  
Electric Vehicle ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Hill Climbing ◽  
Neighborhood Search ◽  
Battery Life ◽  
Routing Problem ◽  
Crossover And Mutation

In this paper, we study an electric vehicle routing problem while considering the constraints on battery life and battery swapping stations. We first introduce a comprehensive model consisting of speed, load and distance to measure the energy consumption and carbon emissions of electric vehicles. Second, we propose a mixed integer programming model to minimize the total costs related to electric vehicle energy consumption and travel time. To solve this model efficiently, we develop an adaptive genetic algorithm based on hill climbing optimization and neighborhood search. The crossover and mutation probabilities are designed to adaptively adjust with the change of population fitness. The hill climbing search is used to enhance the local search ability of the algorithm. In order to satisfy the constraints of battery life and battery swapping stations, the neighborhood search strategy is applied to obtain the final optimal feasible solution. Finally, we conduct numerical experiments to test the performance of the algorithm. Computational results illustrate that a routing arrangement that accounts for power consumption and travel time can reduce carbon emissions and total logistics delivery costs. Moreover, we demonstrate the effect of adaptive crossover and mutation probabilities on the optimal solution.

scholarly journals Research on Optimization of Electric Vehicle Routing Problem With Time Window

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 146707-146718
Author(s):  
Hao Li ◽  
Zhenping Li ◽  
Li Cao ◽  
Ruoda Wang ◽  
Mu Ren
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Routing Problem
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