scholarly journals A review on the electric vehicle routing problems: Variants and algorithms

2021 ◽  
Author(s):  
Hu Qin ◽  
Xinxin Su ◽  
Teng Ren ◽  
Zhixing Luo
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problems ◽  
Location Routing Problem ◽  
Routing Problems ◽  
Routing Problem ◽  
Delivery Problem ◽  
Pickup And Delivery Problem ◽  
The Past ◽  
Location Routing ◽  
Comprehensive Survey

AbstractOver the past decade, electric vehicles (EVs) have been considered in a growing number of models and methods for vehicle routing problems (VRPs). This study presents a comprehensive survey of EV routing problems and their many variants. We only consider the problems in which each vehicle may visit multiple vertices and be recharged during the trip. The related literature can be roughly divided into nine classes: Electric traveling salesman problem, green VRP, electric VRP, mixed electric VRP, electric location routing problem, hybrid electric VRP, electric dial-a-ride problem, electric two-echelon VRP, and electric pickup and delivery problem. For each of these nine classes, we focus on reviewing the settings of problem variants and the algorithms used to obtain their solutions.

scholarly journals Cost Optimisation in Freight Distribution with Cross-Docking: N-Echelon Location Routing Problem

1970 ◽  
Vol 24 (2) ◽  
pp. 143-149 ◽  
Author(s):  
Jesus Gonzalez-Feliu
Keyword(s):  
Literature Review ◽  
Vehicle Routing ◽  
Cost Reduction ◽  
Operational Research ◽  
Freight Transportation ◽  
Vehicle Routing Problems ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Cross Docking ◽  
Location Routing

Freight transportation constitutes one of the main activities that influence the economy and society, as it assures a vital link between suppliers and customers and represents a major source of employment. Multi-echelon distribution is one of the most common strategies adopted by the transportation companies in an aim of cost reduction. Although vehicle routing problems are very common in operational research, they are essentially related to single-echelon cases. This paper presents the main concepts of multi-echelon distribution with cross-docks and a unified notation for the N-echelon location routing problem. A literature review is also presented, in order to list the main problems and methods that can be helpful for scientists and transportation practitioners.

A Two-Phase Meta Heuristic Approach to the Location-Routing Problem for Transportation Network Planning

2013 ◽  
Vol 361-363 ◽  
pp. 1900-1905 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Ant Colony Optimization ◽  
Facility Location ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Transportation Network ◽  
Ant Colony Optimization Algorithm ◽  
Two Phase ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

In this paper we consider the location-routing problem which combines the facility location and the vehicle routing decisions. In this type of problem, we have to determine the location of facilities within a set of possible locations and routes of the vehicles to meet the demands of number of customers. Since the location-routing problem is NP-hard, it is difficult to obtain optimal solution within a reasonable computational time. Therefore, a two-phase ant colony optimization algorithm is developed which solves facility location problem and vehicle routing problem hierarchically. Its performance is examined through a comparative study. The experimental results show that the proposed ant colony optimization algorithm can be a viable solution method for the general transportation network planning.

scholarly journals An Inverse Robust Optimisation Approach for a Class of Vehicle Routing Problems under Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Liang Sun ◽  
Bing Wang
Keyword(s):  
Vehicle Routing ◽  
Transportation Cost ◽  
Test Problems ◽  
Vehicle Routing Problems ◽  
Road Transportation ◽  
Robust Optimisation ◽  
Routing Problems ◽  
Routing Problem ◽  
Trade Off ◽  
Total Transportation Cost

There is a trade-off between the total penalty paid to customers (TPC) and the total transportation cost (TTC) in depot for vehicle routing problems under uncertainty (VRPU). The trade-off refers to the fact that the TTC in depot inevitably increases when the TPC decreases andvice versa. With respect to this issue, the vehicle routing problem (VRP) with uncertain customer demand and travel time was studied to optimise the TPC and the TTC in depot. In addition, an inverse robust optimisation approach was proposed to solve this kind of VRPU by combining the ideas of inverse optimisation and robust optimisation so as to improve both the TPC and the TTC in depot. The method aimed to improve the corresponding TTC of the robust optimisation solution under the minimum TPC through minimising the adjustment of benchmark road transportation cost. According to the characteristics of the inverse robust optimisation model, a genetic algorithm (GA) and column generation algorithm are combined to solve the problem. Moreover, 39 test problems are solved by using an inverse robust optimisation approach: the results show that both the TPC and TTC obtained by using the inverse robust optimisation approach are less than those calculated using a robust optimisation approach.

scholarly journals A New Plant Intelligent Behaviour Optimisation Algorithm for Solving Vehicle Routing Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Godfrey Chagwiza
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Future Research ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Optimisation Algorithm ◽  
Input Parameters ◽  
Problem Instances

A new plant intelligent behaviour optimisation algorithm is developed. The algorithm is motivated by intelligent behaviour of plants and is implemented to solve benchmark vehicle routing problems of all sizes, and results were compared to those in literature. The results show that the new algorithm outperforms most of algorithms it was compared to for very large and large vehicle routing problem instances. This is attributed to the ability of the plant to use previously stored memory to respond to new problems. Future research may focus on improving input parameters so as to achieve better results.

Variable Fixing for Two-Arc Sequences in Branch-Price-and-Cut Algorithms on Path-Based Models

2020 ◽  
Vol 54 (5) ◽  
pp. 1170-1188 ◽  
Author(s):  
Guy Desaulniers ◽  
Timo Gschwind ◽  
Stefan Irnich
Keyword(s):  
Vehicle Routing ◽  
Time Windows ◽  
Solution Process ◽  
Mixed Integer ◽  
Linear Programs ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Benchmark Instances ◽  
Variable Fixing

Variable fixing by reduced costs is a popular technique for accelerating the solution process of mixed-integer linear programs. For vehicle-routing problems solved by branch-price-and-cut algorithms, it is possible to fix to zero the variables associated with all routes containing at least one arc from a subset of arcs determined according to the dual solution of a linear relaxation. This is equivalent to removing these arcs from the network used to generate the routes. In this paper, we extend this technique to routes containing sequences of two arcs. Such sequences or their arcs cannot be removed directly from the network because routes traversing only one arc of a sequence might still be allowed. For some of the most common vehicle-routing problems, we show how this issue can be overcome by modifying the route-generation labeling algorithm in order to remove indirectly these sequences from the network. The proposed acceleration strategy is tested on benchmark instances of the vehicle-routing problem with time windows (VRPTW) and four variants of the electric VRPTW. The computational results show that it yields a significant speedup, especially for the most difficult instances.

VRoptBees

2018 ◽  
Vol 7 (1) ◽  
pp. 32-56
Author(s):  
Thiago A.S. Masutti ◽  
Leandro Nunes de Castro
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Optimization Problems ◽  
The Other ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
Biological Phenomena ◽  
The Traveling Salesman Problem

Combinatorial optimization problems are broadly studied in the literature. On the one hand, their challenging characteristics, such as the constraints and number of potential solutions, inspires their use to test new solution techniques. On the other hand, the practical application of these problems provides support of daily tasks of people and companies. Vehicle routing problems constitute a well-known class of combinatorial optimization problems, from which the Traveling Salesman Problem (TSP) is one of the most elementary ones. TSP corresponds to finding the shortest route that visits all cities within a path returning to the start city. Despite its simplicity, the difficulty in finding its exact solution and its direct application in practical problems in multiple areas make it one of the most studied problems in the literature. Algorithms inspired by biological phenomena are being successfully applied to solve optimization tasks, mainly combinatorial optimization problems. Those inspired by the collective behavior of insects produce good results for solving such problems. This article proposes the VRoptBees, a framework inspired by honeybee behavior to tackle vehicle routing problems. The framework provides a flexible and modular tool to easily build solutions to vehicle routing problems. Together with the framework, two examples of implementation are described, one to solve the TSP and the other to solve the Capacitated Vehicle Routing Problem (CVRP). Tests were conducted with benchmark instances from the literature, showing competitive results.

The Research of Vehicle Routing Problem With Time Window for Changsha Yunda Express in Kaifu District

2013 ◽  
Vol 336-338 ◽  
pp. 2525-2528
Author(s):  
Zhong Liu
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Distribution Center ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Service Levels ◽  
Shortest Distance

For express companies' distribution center, optimizing the vehicle routing can improve service levels and reduce logistics costs. This paper combines the present vehicle routing situation of Chang Sha Yunda Express in KaiFu area with the specific circumstances to analyze. A model of the vehicle routing problem with time window for the shortest distance was built and then use genetic algorithm to solve the problem. Its application showed that the method can effectively solve the current vehicle routing problems.

scholarly journals An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Solution Method ◽  
Programming Model ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitatedp-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

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