A Soft Computing-Based Idea Applied to the Truck and Trailer Routing Problem

2014 ◽  
pp. 245-259
Author(s):  
Isis Torres Pérez ◽  
Alejandro Rosete Suárez ◽  
Carlos Cruz-Corona ◽  
José L. Verdegay
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Soft Computing ◽  
Real World ◽  
Combinatorial Optimization Problem ◽  
Decision Makers ◽  
Linguistic Information ◽  
Routing Problem ◽  
Problem Model ◽  
Subjective Knowledge

Techniques based on Soft Computing are useful to model and solve real-world problems where decision makers use subjective knowledge or linguistic information when making decisions, measuring parameters, objectives, and constraints, and even when modeling the problem. In many problems in transport and logistics, it is necessary to take into account that the available knowledge about some data and parameters of the problem model is imprecise or uncertain. Truck and Trailer Routing Problem, TTRP, is one of most recent and interesting problems in transport routing planning. TTRP is a combinatorial optimization problem, and it is computationally more difficult to solve than the known Vehicle Routing Problem, VRP. Most of models used in the literature assume that the data available is accurate; but this consideration does not correspond with reality. For this reason, it is appropriate to focus research toward defining TTRP models for incorporating the uncertainty present in their data. The aims of the present chapter are: a) to provide a study on the Truck and Trailer Routing Problem that serves as help to researchers interested on this topic and b) to present an approach using techniques of Soft Computing to solve this problem.

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.

Models and Solutions for Truck and Trailer Routing Problems

2013 ◽  
Vol 4 (2) ◽  
pp. 31-43 ◽  
Author(s):  
Isis Torres Pérez ◽  
José Luis Verdegay ◽  
Carlos Cruz Corona ◽  
Alejandro Rosete Suárez
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimization Problem ◽  
Combinatorial Optimization Problem ◽  
Practical Relevance ◽  
Routing Problem ◽  
Considerable Difficulty ◽  
Geographically Dispersed ◽  
Optimal Set

This paper is a survey about of the Truck and Trailer Routing Problem. The Truck and Trailer Routing Problem is an extension of the well-known Vehicle Routing Problem. Defined recently, this problem consists in designing the optimal set of routes for fleet of vehicles (trucks and trailers) in order to serve a given set of geographically dispersed customers. Since TTRP itself is a very difficult combinatorial optimization problem are usually tackled by metaheuristics. The interest in Truck and Trailer Routing Problem is motivated by its practical relevance as well as by its considerable difficulty. The goal of this paper is to show a study on the TTRP and the metaheuristics used for to solve it.

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.

scholarly journals Capacitated vehicle routing problem model for carriers

2018 ◽  
Vol 12 ◽  
Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Route Planning ◽  
Test Problems ◽  
Optimal Route ◽  
Routing Problem ◽  
Problem Model ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

scholarly journals New Instances for Maximum Weight Independent Set From a Vehicle Routing Application

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Yuanyuan Dong ◽  
Andrew V. Goldberg ◽  
Alexander Noe ◽  
Nikos Parotsidis ◽  
Mauricio G. C. Resende ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Independent Set ◽  
Maximum Weight ◽  
Routing Problem ◽  
Independent Set Problem ◽  
Maximum Weight Independent Set ◽  
Large Size

AbstractWe present a set of new instances of the maximum weight independent set problem. These instances are derived from a real-world vehicle routing problem and are challenging to solve in part because of their large size. We present instances with up to 881 thousand nodes and 383 million edges.

scholarly journals Solving Practical Vehicle Routing Problem with Time Windows Using Metaheuristic Algorithms

1970 ◽  
Vol 24 (4) ◽  
pp. 343-351 ◽  
Author(s):  
Filip Taner ◽  
Ante Galić ◽  
Tonči Carić
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Iterated Local Search ◽  
Metaheuristic Algorithms ◽  
Benchmark Problems ◽  
Routing Problem ◽  
Constructive Heuristics ◽  
Initial Feasible Solution

This paper addresses the Vehicle Routing Problem with Time Windows (VRPTW) and shows that implementing algorithms for solving various instances of VRPs can significantly reduce transportation costs that occur during the delivery process. Two metaheuristic algorithms were developed for solving VRPTW: Simulated Annealing and Iterated Local Search. Both algorithms generate initial feasible solution using constructive heuristics and use operators and various strategies for an iterative improvement. The algorithms were tested on Solomon’s benchmark problems and real world vehicle routing problems with time windows. In total, 44 real world problems were optimized in the case study using described algorithms. Obtained results showed that the same distribution task can be accomplished with savings up to 40% in the total travelled distance and that manually constructed routes are very ineffective.

scholarly journals POPMUSIC for a real-world large-scale vehicle routing problem with time windows

2009 ◽  
Vol 60 (7) ◽  
pp. 934-943 ◽  
Author(s):  
A Ostertag ◽  
K F Doerner ◽  
R F Hartl ◽  
E D Taillard ◽  
P Waelti
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Time Windows ◽  
Routing Problem

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.

Sign in / Sign up

Export Citation Format

Share Document