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Maintaining Soft Arc Consistencies in BnB-ADOPT +  during Search

  • Patricia Gutierrez
  • Jimmy H. M. Lee
  • Ka Man Lei
  • Terrence W. K. Mak
  • Pedro Meseguer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8124)

Abstract

Gutierrez and Meseguer show how to enforce consistency in BnB-ADOPT +  for distributed constraint optimization, but they consider unconditional deletions only. However, during search, more values can be pruned conditionally according to variable instantiations that define subproblems. Enforcing consistency in these subproblems can cause further search space reduction. We introduce efficient methods to maintain soft arc consistencies in every subproblem during search, a non trivial task due to asynchronicity and induced overheads. Experimental results show substantial benefits on three different benchmarks.

Keywords

Cost Function Variable Assignment Conditional Deletion Cost Message Unary Cost 
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 2013

Authors and Affiliations

  • Patricia Gutierrez
    • 1
  • Jimmy H. M. Lee
    • 2
  • Ka Man Lei
    • 2
  • Terrence W. K. Mak
    • 3
  • Pedro Meseguer
    • 1
  1. 1.IIIA - CSICUniversitat Autònoma de BarcelonaBellaterraSpain
  2. 2.Department of Computer Science and EngineeringThe Chinese University of Hong KongShatinHong Kong
  3. 3.NICTA Victoria Laboratory & University of MelbourneAustralia

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