Modelación matemática del problema de ruteo de vehículos con restricciones de múltiples depósitos, flota heterogénea de vehículos y ventanas de tiempos
In the present work we propose a mathematical method of mixed integer linear programming (MIP) to solve a vehicle routing problem with constrains of multiples depots, heterogeneous fleet of vehicles and time windows programmed in GAMS, a General Algebraic modeling Software. One of the difficulties p...
- Autores:
-
Herazo Padilla, Nilson
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2012
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/1422
- Acceso en línea:
- https://hdl.handle.net/11323/1422
https://repositorio.cuc.edu.co/
- Palabra clave:
- Lógica
Matemática
Probabilidades
Modelación
Ingenieria industrial
Depósitos
Logic
Mathematics
probability
Modeling
Industrial engineer
- Rights
- openAccess
- License
- Atribución – No comercial – Compartir igual
Summary: | In the present work we propose a mathematical method of mixed integer linear programming (MIP) to solve a vehicle routing problem with constrains of multiples depots, heterogeneous fleet of vehicles and time windows programmed in GAMS, a General Algebraic modeling Software. One of the difficulties presented in approximated methods proposed to solve vehicle routing problems is that the quality of their solutions is not always known and they often are only applicable to solve the specific problems for which they were designed. The presented model not only is capable to solve problems such MDHVRPTW to which it was originally designed but it’s also capable to solve less constrained problems like VRPTW, HVRPTW and MDVRPTW. Another valuable contribution of the presented model is that the model can work as a pattern to prove the quality of the solutions of the approximated methods. The model solve to optimality benchmark problems of 5 and 10 nodes and generates solutions near to optimality with a gap of less than 3% to 15 and 20 nodes problems. |
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