scholarly journals Electric vehicle routing problem with backhauls considering the location of charging stations and the operation of the electric power distribution system

TecnoLógicas ◽  
2019 ◽  
Vol 22 (44) ◽  
pp. 1-20 ◽  
Author(s):  
Luis Carlos Cubides ◽  
Andrés Arias Londoño ◽  
Mauricio Granada Echeverri
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Power Distribution ◽  
Vehicle Routing Problem ◽  
Distribution Network ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Routing Problem ◽  
Battery Capacity ◽  
Charging Stations

Logistics companies are largely encouraged to make greener their operations through an efficient solution with electric vehicles (EVs). However, the driving range is one of the limiting aspects for the introduction of EVs in logistics fleet, due to the low capacity provided by the batteries to perform the routes. In this regards, it is necessary to set up a framework to virtually increase this battery capacity by locating EV charging stations (EVCSs) along the transportation network for the completion of their routes. By the other side, the Distribution Network Operators (DNOs) express the concern associated with the inclusion of new power demands to be attended (installation of EVCSs) in the Distribution Network (DN), without reducing the optimal power supply management for the end-users. Under these circumstances, in this paper the Electric Vehicle Routing Problem with Backhauls and optimal operation of the Distribution Network (EVRPB-DN) is introduced and formulated as a mixed-integer linear programming model, considering the operation of the DN in conditions of maximum power demand. Different candidate points for the EVs charging are considered to recharge the battery at the end of the linehaul route or during the backhaul route. The problem is formulated as a multi-objective approach where the transportation and power distribution networks operation are modeled. The performance and effectiveness of the proposed formulation is tested in VRPB instance datasets and DN test systems from the literature. Pareto fronts for each instance are presented, using the ε-constraint methodology.

scholarly journals A Linearized Approach for the Electric Light Commercial Vehicle Routing Problem Combined with Charging Station Siting and Power Distribution Network Assessment

2021 ◽  
Vol 11 (11) ◽  
pp. 4870
Author(s):  
Andrés Arias-Londoño ◽  
Walter Gil-González ◽  
Oscar Danilo Montoya
Keyword(s):  
Vehicle Routing ◽  
Power Distribution ◽  
Vehicle Routing Problem ◽  
Distribution System ◽  
Mixed Integer ◽  
Routing Problem ◽  
Power Distribution System ◽  
Charging Station ◽  
Battery Capacity ◽  
Electric Light

Transportation electrification has demonstrated a significant position on power utilities and logistic companies, in terms of assets operation and management. Under this context, this paper presents the problem of seeking feasible and good quality routes for electric light commercial vehicles considering battery capacity and charging station siting on the power distribution system. Different transportation patterns for goods delivery are included, such as the capacitated vehicle routing problem and the shortest path problem for the last mile delivery. To solve the problem framed within a mixed integer linear mathematical model, the GAMS software is used and validated on a test instance conformed by a 19-customer transportation network, spatially combined with the IEEE 34 nodes power distribution system. The sensitivity analysis, performed during the computational experiments, show the behavior of the variables involved in the logistics operation, i.e., routing cost for each transport pattern. The trade-off between the battery capacity, the cost of the charging station installation, and energy losses on the power distribution system is also shown, including the energy consumption cost created by the charging operation.

scholarly journals Time-Dependent Electric Vehicle Routing Problem with Time Windows and Path Flexibility

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Li Wang ◽  
Shuai Gao ◽  
Kai Wang ◽  
Tong Li ◽  
Lin Li ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Optimal Path ◽  
Travel Speed ◽  
Path Selection ◽  
Time Dependent ◽  
Mixed Integer ◽  
Routing Problem

With energy and environmental issues becoming increasingly prominent, electric vehicles (EVs) have become the important transportation means in the logistics distribution. In the real-world urban road network, there often exist multiple paths between any two locations (depot, customer, and charging station) since the time-dependent travel times. That is, the travel speed of an EV on each path may be different during different time periods, and thus, this paper explicitly considers path selection between two locations in the time-dependent electric vehicle routing problem with time windows, denoted as path flexibility. Therefore, the integrated decision-making should include not only the routing plan but also the path selection, and the interested problem of this paper is a time-dependent electric vehicle routing problem with time windows and path flexibility (TDEVRP-PF). In order to determine the optimal path between any two locations, an optimization model is established with the goal of minimizing the distance and the battery energy consumption associated with travel speed and cargo load. On the basis of the optimal path model, a 0-1 mixed-integer programming model is then formulated to minimize the total travel distance. Hereinafter, an improved version of the variable neighborhood search (VNS) algorithm is utilized to solve the proposed models, in which multithreading technique is adopted to improve the solution efficiency significantly. Ultimately, several numerical experiments are carried out to test the performance of VNS with a view to the conclusion that the improved VNS is effective in finding high-quality distribution schemes consisted of the distribution routes, traveling paths, and charging plans, which are of practical significance to select and arrange EVs for logistics enterprises.

scholarly journals The Mobile Charging Vehicle Routing Problem with Time Windows and Recharging Services

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Shaohua Cui ◽  
Hui Zhao ◽  
Hui Chen ◽  
Cuiping Zhang
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicles ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Routing Problem ◽  
Battery Electric Vehicles ◽  
Battery Capacity

For the environmental friendliness of the technology on battery electric vehicles, there is growing attention on it. However, the market share of battery electric vehicles remains low due to the range anxiety. As a remedy, the mobile charging services could offer charging service at any time or locations requested. For profitability of the services, the operator should route the charging vehicles in a more efficient manner. For this consideration, we formulate the mobile charging vehicle routing problem as a mixed integer linear program based on the classical vehicle routing problem with time windows. To demonstrate the model, test instances are designed and computational results are presented. In order to examine the change of the number of mobile charging vehicles and travel distance, sensitivity analyses, such as battery capacity and recharging rate, are performed. The results show that larger battery capacity, quicker charging rate, or higher service efficiency could decrease the number of mobile charging vehicles and total traveled distances, respectively.

scholarly journals An Adaptive Memetic Algorithm for Dynamic Electric Vehicle Routing Problem with Time-Varying Demands

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Na Wang ◽  
Yihao Sun ◽  
Hongfeng Wang
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Memetic Algorithm ◽  
Dynamic Environment ◽  
Time Varying ◽  
Routing Problem ◽  
Battery Capacity ◽  
Encoding Strategy ◽  
Local Search Operator

Dynamic electric vehicle routing problem (DEVRP) is an extension of the electric vehicle routing problem (EVRP) into dynamic logistical transportation system such that the demand of customer may change over time. The routing decision of DEVRP must concern with the driving range limitation of electric vehicle (EV) in a dynamic environment since both load degree and battery capacity are variable according to the time-varying demands. This paper proposes an adaptive memetic algorithm, where a special encoding strategy, an adaptive local search operator, and an economical random immigrant scheme are employed in the framework of evolutionary algorithm, to solve DEVRP efficiently. Numeric experiments are carried out upon a series of test instances that are constructed from a stationary VRP benchmark. The computational results show that the proposed algorithm is more effective in finding high-quality solution than several peer algorithms as well as significant in improving the capacity of the routing plan of EVs in dynamic transportation environment.

scholarly journals SVND Enhanced Metaheuristic for Plug-In Hybrid Electric Vehicle Routing Problem

2020 ◽  
Vol 10 (2) ◽  
pp. 441 ◽  
Author(s):  
Xiaohui Li ◽  
Xuemin Shi ◽  
Yi Zhao ◽  
Huagang Liang ◽  
Yuan Dong
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Hybrid Electric Vehicle ◽  
Low Cost ◽  
Mixed Integer ◽  
Routing Problem ◽  
Routing Optimization ◽  
Planning Optimization ◽  
Battery Capacity ◽  
Hybrid Electric

Plug-in Hybrid Electric Vehicles (PHEVs), as a new type of environmental-friendly low cost transportation, have attracted growing interests for logistics. The path-planning optimization for PHEV has become a major challenge. In fact, PHEV-based routing optimization is a type of hybrid vehicle routing problem (HVRP). Compared with the traditional Traveling Salesman Problem (TSP) and Vehicle Routing Problem (VRP), the PHEV routing problem should consider more constraints, such as time limits, capacity constraints (including fuel tank capacity and battery capacity), electric stations, fuel stations and so forth. In this paper, a Mixed Integer Linear Programming formulation is presented and a novel hybrid metaheuristic approach (HMA_SVND) is proposed. Our method is a combination of memetic algorithm (MA), sequential variable neighborhood descent (SVND) and a revised 2_opt method. Comparative studies show that our proposed method outperformed previous works.

The electric vehicle routing problem with shared charging stations

2018 ◽  
Vol 26 (4) ◽  
pp. 1211-1243 ◽  
Author(s):  
Çağrı Koç ◽  
Ola Jabali ◽  
Jorge E. Mendoza ◽  
Gilbert Laporte
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Routing Problem ◽  
Charging Stations

scholarly journals Electric Vehicle Routing Problem in Urban Logistics

2021 ◽  
Vol 6 (4) ◽  
pp. 61
Author(s):  
Yiwei Lu
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Vehicle Routing Problem ◽  
Real Life ◽  
Routing Problem ◽  
Electric Vehicle Charging ◽  
New Research ◽  
Charging Stations ◽  
The Impact

<p><span lang="EN-US">Due to the impact of global warming, diesel locomotives that use fossil energy as fuel are gradually being replaced by electric vehicles. At present, many countries at home and abroad are actively promoting the development of the electric vehicle industry in response to the call of the Paris Agreement. However, electric vehicles have a maximum mileage limit, so the reasonable layout of electric vehicle charging stations is also a problem to be solved today. In this article, the author analyzes the research background of the electric vehicle routing problem. After introducing several new research directions in the current electric vehicle routing problem, we propose an optimization algorithm for solving those types of problem. It brings certain theoretical significance for future generations to solve the problem of electric vehicle routing in real life.</span></p>

A hybrid algorithm for electric vehicle routing problem with nonlinear charging

2021 ◽  
pp. 1-20
Author(s):  
Jiawen Deng ◽  
Junqing Li ◽  
Chengyou Li ◽  
Yuyan Han ◽  
Qingsong Liu ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Vehicle Routing Problem ◽  
Hybrid Algorithm ◽  
High Performance ◽  
Time Windows ◽  
Routing Problem ◽  
Battery Degradation ◽  
Encoding Method ◽  
Charging Stations

This paper investigates the electric vehicle routing problem with time windows and nonlinear charging constraints (EVRPTW-NL), which is more practical due to battery degradation. A hybrid algorithm combining an improved differential evolution and several heuristic (IDE) is proposed to solve this problem, where the weighted sum of the total trip time and customer satisfaction value is minimized. In the proposed algorithm, a special encoding method is presented that considers charging stations features. Then, a battery charging adjustment (BCA) strategy is integrated to decrease the charging time. Furthermore, a novel negative repair strategy is embedded to make the solution feasible. Finally, several instances are generated to examine the effectiveness of the IDE algorithm. The high performance of the IDE algorithm is shown in comparison with two efficient algorithms.

A Multi-Period Evacuation Vehicle Routing Problem Model

2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang
Keyword(s):  
Vehicle Routing ◽  
Public Transportation ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
High Water ◽  
Mixed Integer ◽  
Routing Problem ◽  
Problem Model ◽  
Proposed Model ◽  
Evacuation Routing

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.

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