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

  • Authors:

  • R. Blanquero;E. Carrizosa

  • Affiliations:

  • Facultad de Matemáticas, Universidad de Sevilla, Seville, Spain 4012;Facultad de Matemáticas, Universidad de Sevilla, Seville, Spain 4012

  • Venue:
  • Journal of Global Optimization
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

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.