scholarly journals C.H. Robinson Uses Heuristics to Solve Rich Vehicle Routing Problems

2021 ◽  
Author(s):  
Ehsan Khodabandeh ◽  
Lawrence V. Snyder ◽  
John Dennis ◽  
Joshua Hammond ◽  
Cody Wanless
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Daily Basis ◽  
Setup Times ◽  
Third Party ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Customer Outcomes ◽  
Practical Constraints

We consider a broad family of vehicle routing problem variants with many complex and practical constraints, known as rich vehicle routing problems, which are faced on a daily basis by C.H. Robinson (CHR). Because CHR has many customers, each with distinct requirements, various routing problems with different objectives and constraints must be solved. We propose a novel framework for solving rich vehicle routing problems, which we demonstrate is effective in solving a variety of different problems. This framework, along with a simple user interface, has been wrapped into a new module and integrated into the company’s transportation planning and execution technology platform. Since its implementation, this new module has outperformed the previously used third-party technologies at CHR, significantly reduced setup times, and improved users’ productivity as well as customer outcomes.

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.

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 Multiple Ant Colony Optimization for Single Depot Multiple Trip Vehicle Routing Problems

10.29007/8tjs ◽  
2018 ◽  
Author(s):  
Zhengmao Ye ◽  
Habib Mohamadian
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Urban Areas ◽  
Ant Colony ◽  
Ant Colony System ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Single Vehicle

The multiple trip vehicle routing problem involves several sequences of routes. Working shift of single vehicle can be scheduled in multiple trips. It is suitable for urban areas where the vehicle has very limited size and capacity over short travel distances. The size and capacity limit also requires the vehicle should be vacated frequently. As a result, the vehicle could be used in different trips as long as the total time or distance is not exceeded. Various approaches are developed to solve the vehicle routing problem (VRP). Except for the simplest cases, VRP is always a computationally complex issue in order to optimize the objective function in terms or both time and expense. Ant colony optimization (ACO) has been introduced to solve the vehicle routing problem. The multiple ant colony system is proposed to search for alternative trails between the source and destination so as to minimize (fuel consumption, distance, time) among numerous geographically scattered routes. The objective is to design adaptive routing so as to balance loads among congesting city networks and to be adaptable to connection failures. As the route number increases, each route becomes less densely packed. It can be viewed as the vehicle scheduling problem with capacity constraints. The proposed scheme is applied to typical cases of vehicle routing problems with a single depot and flexible trip numbers. Results show feasibility and effectiveness of the approach.

scholarly journals A Contemporary Recapitulation of Major Findings on Vehicle Routing Problems : Models and Methodologies

2019 ◽  
Vol 8 (2S4) ◽  
pp. 581-585
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Distribution Systems ◽  
Time Windows ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Innovative Solutions ◽  
The Common ◽  
Ultimate Objective

In introdusing and designing innovative solutions to the problems related to transportation and distribution systems is a contemporary area in logistics. The ultimate objective of this paper is to initiate a thought provoking discusion on Vehicle Routing Problems (VRP) along with its modifications or changes which incorporates recent model developments and improvements. Both in operational research and computer science, VRP is a combinatorial optimization issue researched at length. Capacitated Vehicle Routing Problem (CVRP), Vehicle Routing Problem with Time Windows (VRPTW), Vehicle Routing Problem with MultiDepot (MDVRP) and other variants are integral components of VRP. In recent times, the areas of VRP categorization has been further discussed, the common constraints have been summarized and model algorithms have been developed. In toto the future model implications of VRP are analyzed and further, it is predicted that the Intelligent Vehicle Routing Problem and Intelligent Heuristic Algorithm would be an important arena of future researches

scholarly journals Overview of fuzzy vehicle routing problems

2020 ◽  
Vol 20 (3) ◽  
pp. 325-331
Author(s):  
Yu. O. Chernyshev ◽  
V. N. Kubil ◽  
A. V. Trebukhin
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Fuzzy Variable ◽  
Optimal Solution ◽  
Fuzzy Programming ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Routing Problem ◽  
Fuzzy Variables ◽  
Fundamental Properties

Introduction. Various algorithms for solving fuzzy vehicle routing problems are considered. The work objective was to study modern methods for the optimal solution to fuzzy, random and rough vehicle routing problems. Materials and Methods. The paper reviews fuzzy vehicle routing problems, existing methods and approaches to their solution. The most effective features of some approaches to solving fuzzy vehicle routing problems considering their specificity, are highlighted. Results. The Fuzzy Vehicle Routing Problem (FVRP) occurs whenever the routing data is vague, unclear, or ambiguous. In many cases, these fuzzy elements can better reflect reality. However, it is very difficult to use Vehicle Routing Problem (VRP) solving algorithms to solve FVRP since several fundamental properties of deterministic problems are no longer fulfilled in FVRP. Therefore, it is required to introduce new models and algorithms of fuzzy programming to solve such problems. Thus, the use of methods of the theory of fuzzy sets will provide successful simulation of the problems containing elements of uncertainty and subjectivity. Discussion and conclusions. As a result of reviewing various methods and approaches to solving vehicle routing problems, it is concluded that the development and study of new solutions come into sharp focus of researchers nowadays, but the degree of elaboration of various options varies. Methods for the optimal solution of FVRP are limited, in general, to some single fuzzy variable. There is a very limited number of papers that consider a large number of fuzzy variables.

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 Current State of Dynamic Vehicle Routing Problems Solved by Ant Colony Optimization Algorithm

2021 ◽  
Vol 15 (3) ◽  
pp. 429-434
Author(s):  
Luka Olivari ◽  
Goran Đukić
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Dynamic Vehicle Routing ◽  
Routing Problems ◽  
Routing Problem ◽  
Solution Methods

Dynamic Vehicle Routing Problem is a more complex version of Vehicle Routing Problem, closer to the present, real-world problems. Heuristic methods are used to solve the problem as Vehicle Routing Problem is NP-hard. Among many different solution methods, the Ant Colony Optimization algorithm is proven to be the efficient solution when dealing with the dynamic version of the problem. Even though this problem is known to the scientific community for decades, the field is extremely active due to technological advancements and the current relevance of the problem. As various sub-types of routing problems and solution methods exist, there is a great number of possible problem-solution combinations and research directions. This paper aims to make a focused review of the current state in the field of Dynamic Vehicle Routing Problems solved by Ant Colony Optimization algorithm, to establish current trends in the field.

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 Waste Collection Vehicle Routing Problem: Literature Review

2015 ◽  
Vol 27 (4) ◽  
pp. 345-358 ◽  
Author(s):  
Hui Han ◽  
Eva Ponce Cueto
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Research Literature ◽  
Arc Routing ◽  
Waste Collection ◽  
Logistics System ◽  
Routing Problems ◽  
Routing Problem ◽  
Node Routing

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in literature. Based on a classification of waste collection (residential, commercial and industrial), firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems) used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP.

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