Usando Herramientas de MILP para Estudiar el Modelo de Selección de Portafolios R&D para Casos de Grandes Carteras de Proyectos en el Sector Social
Igor Litvinchev, Fernando López Irarragorri, Miguel Mata Pérez and Elisa Schaeffer
Postgraduate Program in Systems Engineering Faculty of Mechanical and Electrical Engineering, UANL San Nicolás de los Garza, Nuevo León, Mexico e–mails: igor@yalma.fime.uanl.mx, ferny@yalma.fime.uanl.mx, miguel@yalma.fime.uanl.mx, elisa@yalma.fime.uanl.mx
Article received on March 10, 2008
Accepted on August 12, 2008
Abstract
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.
Keywords: R & D projects portfolios, mixed integer programming, multi–objective optimization.
Resumen
En este trabajo se presenta un modelo de programación lineal entera mixta (MILP) para el problema del portafolio de proyectos públicos R & D bi–objetivo. El enfoque propuesto provee un punto medio entre el impacto y el número de los proyectos. Se consideran técnicas de relajación Lagrangiana para obtener cotas fácilmente calculables para los valores objetivos. La experimentación muestra que puede obtenerse una solución en menos de un minuto incluso para casos de carteras de más de 25,000 proyectos propuestos. Esto implica una mejora significativa a los enfoques previos que resuelven eficientemente casos con sólo algunos cientos de proyectos.
Palabras clave: Portafolios de proyectos, programación entera mixta, optimización multiobjetivo.
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]]>Acknowledgments
The work of the first author was partially funded by CONACyT (grant number 61343) while F. López and E. Schaeffer were supported by PROMEP (grant number 103,5/07/2523).
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