Artículo
Continuous location problems and Big Triangle Small Triangle: constructing better bounds
Autor/es | Blanquero Bravo, Rafael
Carrizosa Priego, Emilio José |
Departamento | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa |
Fecha de publicación | 2009-11 |
Fecha de depósito | 2016-10-20 |
Publicado en |
|
Resumen | The Big Triangle Small Triangle method has shown to be a powerful global optimization procedure to address continuous location problems. In the paper published in J. Global Optim. (37:305–319, 2007), Drezner proposes a ... The Big Triangle Small Triangle method has shown to be a powerful global optimization procedure to address continuous location problems. In the paper published in J. Global Optim. (37:305–319, 2007), Drezner proposes a rather general and effective approach for constructing the bounds needed. Such bounds are obtained by using the fact that the objective functions in continuous location models can usually be expressed as a difference of convex functions. In this note we show that, exploiting further the rich structure of such objective functions, alternative bounds can be derived, yielding a significant improvement in computing times, as reported in our numerical experience. |
Agencias financiadoras | Ministerio de Educación y Ciencia (MEC). España Junta de Andalucía |
Identificador del proyecto | MTM2005-09362-C03-01
FQM-329 |
Cita | Blanquero Bravo, R. y Carrizosa Priego, E.J. (2009). Continuous location problems and Big Triangle Small Triangle: constructing better bounds. Journal of Global Optimization, 45 (3), 389-402. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
Continuous location problems and ... | 199.0Kb | [PDF] | Ver/ | |