Modelos e algoritmos para problemas integrados de roteamento e carregamento de veículos

The object of this study are combined problems of the Vehicle Routing Problem and the Container Loading Problem, recently addressed as Integrated Vehicle Routing and Loading Problems. In these problems, the objective is to optimize simultaneously the planning of the vehicles routes and the arrangeme...

Descripción completa

Detalles Bibliográficos
Autor: Junqueira, Leonardo
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2013
País:Brasil
Institución:Universidade Federal de São Carlos (UFSCAR)
Repositorio:Repositório Institucional da UFSCAR
Idioma:portugués
OAI Identifier:oai:repositorio.ufscar.br:20.500.14289/3424
Acceso en línea:https://repositorio.ufscar.br/handle/20.500.14289/3424
Access Level:acceso abierto
Palabra clave:Pesquisa operacional
Otimização combinatória
Modelagem matemática
Métodos heurísticos
Roteamento de veículos
Carregamento de contêineres
Problemas integrados de roteamento e carregamento de veículos
Vehicle routing
Container loading
Integrated vehicle routing and loading problems
Combinatorial optimization
Heuristic methods
ENGENHARIAS::ENGENHARIA DE PRODUCAO
Descripción
Sumario:The object of this study are combined problems of the Vehicle Routing Problem and the Container Loading Problem, recently addressed as Integrated Vehicle Routing and Loading Problems. In these problems, the objective is to optimize simultaneously the planning of the vehicles routes and the arrangement of the cargo inside them, while considering a series of practical constraints from both vehicle routing and container loading. The objectives of this study are: (i) to study the integration between the Vehicle Routing Problem and the Container Loading Problem; (ii) to develop mathematical programming models to represent Integrated Vehicle Routing and Loading Problems; (iii) to develop and implement heuristics and metaheuristics to solve some of these problems; (iv) to analyze and compare the performance of the proposed models, by means of modeling languages and optimization solvers, as well as the heuristic methods, when solving instances from the literature and real-world situations. Besides being hard and relatively less studied problems, the main reason for this study is that with effective solution methods for optimizing the vehicle routing and the cargo loading, operational and tactical decisions could be made with more reliability, accuracy, quickness and with less uncertainty in real situations, besides of an improved use of the staff tasked to load and unload the cargo. On the other hand, these methods can also be usefull to reduce fixed and variable costs in a company that might use them. Computational experiments with some of the proposed models were performed with an optimization software and randomly generated instances. The results show that the models are consistent and properly represent the practical situations treated, although this approach (in its current version) is limited to solve to optimality only problems of moderate size, that is, situations with few customers, few vehicles, and mainly with a relatively reduced number of possible positions to load the boxes. This has motivated the development of heuristic and metaheuristic methods to solve more realistic vehicle routing and loading problems. The algorithms are based on the combination of classical heuristics from both the vehicle routing and container loading literatures, as well as two metaheuristic strategies, and their use in more elaborate procedures. Although these approaches cannot assure optimal solutions for the respective problems, they are relatively simple, fast enough to solve real instances, flexible enough to include practical considerations, and normally assure relatively good solutions in acceptable computational times in practice. Computational experiments were performed with these methods considering instances based on the vehicle routing literature and actual customers orders, as well as instances based on a real-world situation where the problem occurs.