Problema de roteamento de veículos com entregas e coletas mistas e janelas de tempo: aplicação em uma empresa da região metropolitana de Curitiba
The Operational Research (OR) is a branch of applied mathematics that has the purpose of modeling real problems in various areas of knowledge. One of the applications with emphasis in OR is the Vehicle Routing Problem (VRP). The objective of the work is to develop a solution approach for the vehicle...
| Autor principal: | Meira, William Hitoshi Tsunoda |
|---|---|
| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2020
|
| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/8144 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: |
The Operational Research (OR) is a branch of applied mathematics that has the purpose of modeling real problems in various areas of knowledge. One of the applications with emphasis in OR is the Vehicle Routing Problem (VRP). The objective of the work is to develop a solution approach for the vehicle routing problem of a haulier from the metropolitan region of Curitiba. The methodology takes into account constraints and characteristics of real scenarios for development and validation of the mathematical model. In particular, the studied problem is characterized as a variant of the VRP, the VRPMPDTW (Vehicle Routing Problem with Mixed Pickup and Delivery and Time Windows). In order to model and solve scenarios of the company, it is used a technique originated from OR, the Mixed Integer Linear Programming (MILP), associated with pre-processing and post-processing algorithms. Additionally, it was developed a human-computer interface in Java to manage scenarios and analyse results. The solver used for mathematical modeling was the IBM ILOG CPLEX Optimization Studio 12.5. Valid results were obtained in non-prohibitive computational time (seconds to few minutes) for typical scenarios of the company. Future contributions may focus on reducing the computational time for scenarios with similar or greater numbers of vehicles and services, |
|---|