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Continuous location problems and Big Triangle Small Triangle: constructing better bounds

 

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Author: Blanquero Bravo, Rafael
Carrizosa Priego, Emilio José
Department: Universidad de Sevilla. Departamento de Estadística e Investigación Operativa
Date: 2009-11
Published in: Journal of Global Optimization, 45 (3), 389-402.
Document type: Article
Abstract: 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.
Cite: 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.
Size: 199.0Kb
Format: PDF

URI: http://hdl.handle.net/11441/47869

DOI: 10.1007/s10898-008-9381-z

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