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A General Scheme for Multiple Lower Bound Computation in Constraint Optimization

  • Rina Dechter
  • Kalev Kask
  • Javier Larrosa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2239)

Abstract

Computing lower bounds to the best-cost extension of a tuple is an ubiquous task in constraint optimization. A particular case of special interest is the computation of lower bounds to all singleton tuples, since it permits domain pruning in Branch and Bound algorithms. In this paper we introduce MCTE(z), a general algorithm which allows the computation of lower bounds to arbitrary sets of tasks. Its time and accuracy grows as a function of z allowing a controlled tradeo. between lower bound accuracy and time and space to fit available resources. Subsequently, a specialization of MCTE(z) called MBTE(z) is tailored to computing lower bounds to singleton tuples. Preliminary experiments on Max-CSP show that using MBTE(z) to guide dynamic variable and value orderings in branch and bound yields a dramatic reduction in the search space and, for some classes of problems, this reduction is highly coste effective producing significant time savings and is competitive against specialized algorithms for Max-CSP.

Keywords

Constraint Satisfaction Soft Constraint Constraint Optimization Constraint Graph Lower Neighbor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Rina Dechter
    • 1
  • Kalev Kask
    • 1
  • Javier Larrosa
    • 2
  1. 1.University of California at Irvine (UCI)California
  2. 2.Universitat Politecnica de Catalunya (UPC)Catalunya

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