scholarly journals Multi-Depot Joint Distribution Vehicle Routing Problem Considering Energy Consumption with Time-Dependent Networks

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2082
Author(s):  
Dengkai Hou ◽  
Houming Fan ◽  
Xiaoxue Ren
Keyword(s):  
Energy Consumption ◽  
Vehicle Routing ◽  
Fuel Consumption ◽  
Vehicle Routing Problem ◽  
Joint Distribution ◽  
Road Network ◽  
Time Dependent ◽  
Neighborhood Search ◽  
Routing Problem ◽  
The Road

This paper studies the multi-depot joint distribution vehicle routing problem considering energy consumption with time-dependent networks (MDJDVRP-TDN). Aiming at the multi-depot joint distribution vehicle routing problem where the vehicle travel time depends on the variation characteristics of the road network speed in the distribution area, considering the influence of the road network on the vehicle speed and the relationship between vehicle load and fuel consumption, a multi-depot joint distribution vehicle routing optimization model is established to minimize the sum of vehicle fixed cost, fuel consumption cost and time window penalty cost. Traditional vehicle routing problems are modeled based on symmetric graphs. In this paper, considering the influence of time-dependent networks on routes optimization, modeling is based on asymmetric graphs, which increases the complexity of the problem. A hybrid genetic algorithm with variable neighborhood search (HGAVNS) is designed to solve the model, in which the nearest neighbor insertion method and Logistic mapping equation are used to generate the initial solution firstly, and then five neighborhood structures are designed to improve the algorithm. An adaptive neighborhood search times strategy is used to balance the diversification and depth search of the population. The effectiveness of the designed algorithm is verified through several groups of numerical instances with different scales. The research can enrich the relevant theoretical research of multi-depot vehicle routing problems and provide the theoretical basis for transportation enterprises to formulate reasonable distribution schemes.

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 Time-Dependent Multi-Depot Heterogeneous Vehicle Routing Problem Considering Temporal–Spatial Distance

2021 ◽  
Vol 13 (9) ◽  
pp. 4674
Author(s):  
Dengkai Hou ◽  
Houming Fan ◽  
Xiaoxue Ren ◽  
Panjun Tian ◽  
Yingchun Lv
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Time Window ◽  
Time Dependent ◽  
Spatial Distance ◽  
Neighborhood Search ◽  
Routing Problem ◽  
Heterogeneous Vehicle Routing Problem ◽  
Search Capability

Aiming at the multi-depot heterogeneous vehicle routing problem under the time-dependent road network and soft time window, considering vehicle fixed cost, time window penalty cost and vehicle transportation cost, an optimization model of time-dependent multi-depot heterogeneous vehicle routing problem is established with the objective of minimizing distribution cost. According to the characteristics of the problem, a hybrid genetic algorithm with variable neighborhood search considering the temporal–spatial distance is designed. Customers are clustered according to the temporal–spatial distance to generate initial solutions, which improves the quality of the algorithm. The depth search capability of the variable neighborhood search algorithm is applied to the local search strategy of the genetic algorithm to enhance the local search capability of the algorithm. An adaptive neighborhood search number strategy and a new acceptance mechanism of simulated annealing are proposed to balance the breadth and depth required for population evolution. The validity of the model and algorithm is verified by several sets of examples of different scales. The research results not only deepen and expand the relevant research on vehicle routing problem, but also provide theoretical basis for logistics enterprises to optimize distribution scheme.

scholarly journals Time-dependent vehicle routing problem with backhaul with FIFO assumption: Variable neighborhood search and mat-heuristic variable neighborhood search algorithms

2021 ◽  
pp. 15-36 ◽  
Author(s):  
Esmaeil Akhondi Bajegani ◽  
Naser Mollaverdi ◽  
Mahdi Alinaghian
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Heuristic Algorithms ◽  
Time Dependent ◽  
Superior Performance ◽  
Neighborhood Search ◽  
Test Problems ◽  
Routing Problem ◽  
Study Results

This paper presents a mathematical model for a single depot, time-dependent vehicle routing problem with backhaul considering the first in first out (FIFO) assumption. As the nature of the problem is NP-hard, variable neighborhood search (VNS) meta-heuristic and mat-heuristic algorithms have been designed. For test problems with large scales, obtained results highlight the superior performance of the mat-heuristic algorithm compared with that of the other algorithm. Finally a case study at the post office of Khomeini-Shahr town, Iran, was considered. Study results show a reduction of roughly 19% (almost 45 min) in the travel time of the vehicle.

scholarly journals The Time-Dependent Vehicle Routing Problem with Time Windows and Road-Network Information

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Hamza Ben Ticha ◽  
Nabil Absi ◽  
Dominique Feillet ◽  
Alain Quilliot ◽  
Tom Van Woensel
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Road Network ◽  
Time Windows ◽  
Time Dependent ◽  
Routing Problem ◽  
Network Information
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