A Clarke and Wright Improved Algorithm to Solve the Vehicle Routing and Traveling Salesman Problem

2016 ◽  
Vol 8 (1) ◽  
pp. 35
Author(s):  
Mamoon Alameen ◽  
Rasha Aljamal ◽  
Sadeq Damrah
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Traveling Salesman ◽  
Exact Methods ◽  
Routing Problem ◽  
Cpu Time ◽  
Shortest Distance ◽  
Transportation Scheduling ◽  
The Given

Vehicle Routing Problem (VRP) and Traveling Salesman Problem (TSP) are well known transportation problems. The problems can be seen in all the industries that involves goods distribution and transportation scheduling. Finding the shortest distance with respect to the given constraint contribute highly to save money and energy consumption. This paper investigates the possibility of creating a cellular application that can provide an instant routing plan through a simple heuristic (Clarke and Wright) in order to avoid the usage of more complicated approaches as metaheuristics and exact methods that normally taking very long CPU time.

The Traveling Salesman Problem, the Vehicle Routing Problem, and Their Impact on Combinatorial Optimization

2010 ◽  
Vol 1 (2) ◽  
pp. 82-92 ◽  
Author(s):  
Gilbert Laporte
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Traveling Salesman ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

An algorithm for the capacitated vehicle routing problem for picking application in manual warehouses

2019 ◽  
Author(s):  
Eleonora Bottani ◽  
Giorgia Casella ◽  
Caterina Caccia ◽  
Roberto Montanari
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Order Picking ◽  
Traveling Salesman ◽  
Manhattan Distance ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Termination Criteria ◽  
Capacitated Vehicle

Given that warehouses play a central role in modern supply chains, this study proposes the application of an algorithm for the capacitated vehicle routing problem (CVRP) based on the two-index vehicle flow formulation developed by Baldacci, Hadjiconstantinou, and Mingozzi (2004) for picking purposes in manual warehouses. The study of Theys et al. (2010) is first used to represent the warehouse using a Steiner traveling salesman problem (TSP). Then, a calculation of the picking tour’s length is obtained applying the Manhattan distance. Finally, the algorithm for the CVRP is solved through a cutting plane with the addition of termination criteria related to the capacity of picker. The study analyzes four different warehouse configurations, processing five picking list each. The analysis is carried out exploiting the commercial software MATLAB®, to determine the solution that minimize distance of the order picking tour. The results obtained in MATLAB® show the effectiveness of the chosen algorithm applied to the context of manual order picking.

The Traveling Salesman Problem, the Vehicle Routing Problem, and Their Impact on Combinatorial Optimization

2012 ◽  
pp. 342-352
Author(s):  
Gilbert Laporte
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Exact Algorithms ◽  
Traveling Salesman ◽  
Routing Problem ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

scholarly journals Optimization for medical logistics robot based on model of traveling salesman problems and vehicle routing problems

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110225
Author(s):  
Hui Jin ◽  
Qingsong He ◽  
Miao He ◽  
Shiqing Lu ◽  
Fangchao Hu ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Order Picking ◽  
Traveling Salesman ◽  
Vehicle Routing Problems ◽  
Traveling Salesman Problems ◽  
Routing Problem ◽  
Problem Model ◽  
Route Length

Fast medicine dispensing system (FMDS) as a kind of medical logistic robot can dispense many drugs for one prescription at the same time. To guarantee the sustainability of drug dispensation, it is required that FMDS replenish drugs rapidly. The traditional order picking model (OPM) is difficult to meet the demand of prompt replenishment. To solve the problems of prolonged refilling route and inefficiency of drugs replenishment, a mixed refilling model based on multiple steps traveling salesman problem model (MTSPM) and vehicle routing problem model (VRPM) is proposed, and it is deployed in two circumstances of FMDS, including temporary replenishment mode (TRM) and concentrate replenishment mode (CRM). It not only meted the demand under different circumstances of drug replenishment but also shortened the refilling route significantly. First, the new pick sets were generated. Then, the orders of pick sets were optimized and the new paths were achieved. When the number of pickings is varied no more than 20, experiment results declared that the refilling route is the shortest by utilizing MTSPM when working under the TRM condition. Comparing MTSPM with OPM, the rate of refilling route length decreased up to 32.18%. Under the CRM condition, the refilling route is the shortest by utilizing VRPM. Comparing VRPM with OPM, the rate of refilling route length decreased up to 58.32%. Comparing VRPM with MTSPM, the rate of refilling route length has dropped more than 43.26%.

Research on Single Distribution Center Logistics Transportation Scheduling Problem Based on Static Road Capacity Constraints

2013 ◽  
Vol 798-799 ◽  
pp. 954-962
Author(s):  
Yu Qiang Chen ◽  
Wei Jun Yang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Economic Value ◽  
Capacity Constraints ◽  
Distribution Center ◽  
Routing Problem ◽  
Road Capacity ◽  
Wide Range ◽  
Transportation Scheduling ◽  
Chaos Genetic Algorithm

Related Vehicle Routing Problem is another form of Vehicle Routing Problem. RVRP also belongs to NP-Hard with a wide range of application areas and major economic value. The research based on single distribution center RVRP with road capacity static constraint, to build a model of single distribution RVRP and propose a kind of chaos genetic algorithm to solve this problem, with experiments verify the feasibility and effectiveness of the algorithm.

scholarly journals Focusing on the Golden Ball Metaheuristic: An Extended Study on a Wider Set of Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
E. Osaba ◽  
F. Diaz ◽  
R. Carballedo ◽  
E. Onieva ◽  
A. Perallos
Keyword(s):  
Genetic Algorithms ◽  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimization Problems ◽  
Traveling Salesman ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
Golden Ball ◽  
The One

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results.

scholarly journals Traveling salesman problem: approach to optimality

2014 ◽  
Vol 15 (2) ◽  
pp. 157-169
Author(s):  
Radosław Jadczak
Keyword(s):  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Decision Problem ◽  
Mathematical Formulation ◽  
Traveling Salesman ◽  
Chinese Postman Problem ◽  
Routing Problem ◽  
Solution Strategies ◽  
Chinese Postman ◽  
Single Vehicle

Abstract Traveling Salesman Problem (TSP) is a basic and one of the most important transportation problems in operational logistics. It is also known in the literature as a Chinese postman problem or single vehicle routing problem. TSP can be shortly described as follows. Vehicle starting from the selected city must visit a set of another cities exactly once and return to the starting city in such a way that the total distance of the route is minimized. In this paper first mathematical formulation of decision problem is presented. Then solution strategies of TSP are shown with selected algorithms as examples. In the last part of article, a computational results of selected methods are presented.

Use of GVRP as a Model of Two Specific Real World Problems and Its Bioinspired Solution

2016 ◽  
pp. 451-469
Author(s):  
Jorge Rodas ◽  
Daniel Azpeitia ◽  
Alberto Ochoa-Zezzatti ◽  
Raymundo Camarena ◽  
Tania Olivier
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Combinatorial Optimization Problem ◽  
Exact Methods ◽  
Routing Problem ◽  
Computing Technique ◽  
Product Delivery ◽  
Soft Computing Technique ◽  
Generalized Vehicle Routing Problem

The aim of this chapter is about the inclusion of real world scenarios, viewed as a Generalized Vehicle Routing Problem (GVRP) model problem, and treated by bio inspired algorithms in order to find optimum routing of product delivery. GVRP is the generalization of the classical Vehicle Routing Problem (VRP) that is well known NP-hard as generalized combinatorial optimization problem with a number of real world applications and a variety of different versions. Due to its complexity, large instances of VRP are hard to solve using exact methods. Thus a solution by a soft computing technique is desired. From a methodological standpoint, the chapter includes four bio inspired algorithms, ant colony optimization and firefly. From an application standpoint, several factors of the generalized vehicle routing are considered from a real world scenario.

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