Using MILP Tools to Study R & D Portfolio Selection Model for Large Instances in Public and Social Sector
In this paper a mixed-integer linear programming (MILP) model is studied for the bi-objective public R & D projects portfolio problem. The proposed approach provides an acceptable compromise between the impact and the number of supported projects. Lagrangian relaxation techniques are considered...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2008 |
| País: | México |
| Recursos: | Universidad Autónoma de Nuevo León |
| Repositorio: | Redalyc-UANL |
| OAI Identifier: | oai:redalyc.org:61513251002 |
| Acesso em linha: | https://www.redalyc.org/articulo.oa?id=61513251002 |
| Access Level: | acceso abierto |
| Palavra-chave: | Computación multi objective optimization R & D projects portfolios mixed integer programming |
| Resumo: | In this paper a mixed-integer linear programming (MILP) model is studied for the bi-objective public R & D projects portfolio problem. The proposed approach provides an acceptable compromise between the impact and the number of supported projects. Lagrangian relaxation techniques are considered to get easy computable bounds for the objectives. The experiments show that a solution can be obtained in less than a minute for instances comprising of up to 25,000 project proposals. This brings significant improvement to the previous approaches that efficiently manage instances of a few hundred projects. |
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