Optimal fleet replacement: A case study on a Spanish urban transport fleet
[EN] Optimizing the average annual cost of a bus fleet has become an increasing concern in transport companies management around the world. Nowadays, there are many tools available to assist managerial decisions, and one of the most used is the cost analysis of the life cycle of an asset, known as `...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/104132 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/104132 |
| Access Level: | acceso abierto |
| Palabra clave: | Fleet replacement Optimization Operation and maintenance costs Transport Life cycle cost analysis Monte Carlo simulation MAQUINAS Y MOTORES TERMICOS |
| Sumario: | [EN] Optimizing the average annual cost of a bus fleet has become an increasing concern in transport companies management around the world. Nowadays, there are many tools available to assist managerial decisions, and one of the most used is the cost analysis of the life cycle of an asset, known as ``life cycle cost¿¿. Characterized by performing deterministic analysis of the situation, it allows the administration to evaluate the process of fleet replacement but is limited by not contemplating certain intrinsic variations related to vehicles and for disregarding variables related to exigencies of fleet use. The main purpose of this study is to develop a combined model of support to asset management based in the association of the life cycle cost tool and the mathematical model of Monte Carlo simulation, by performing a stochastic analysis considering both age and average annual mileage for optimum vehicle replacement. The utilized method was applied in a Spanish urban transport fleet, and the results indicate that the use of the stochastic model was more effective than the use of the deterministic model. |
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