AND/OR branch-and-bound search for pure 0/1 integer linear programming problems

  • Authors:
  • Radu Marinescu;Rina Dechter

  • Affiliations:
  • School of Information and Computer Science, University of California, Irvine, CA;School of Information and Computer Science, University of California, Irvine, CA

  • Venue:
  • CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
  • Year:
  • 2006

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Abstract

AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sensitivity to the structure of the model, which can translate into exponential time savings for search algorithms. In this paper we extend the recently introduced AND/OR Branch-and-Bound algorithm (AOBB) [1] for solving pure 0/1 Integer Linear Programs [2]. Since the variable selection can have a dramatic impact on search performance, we introduce a new dynamic AND/OR Branch-and-Bound algorithm able to accommodate variable ordering heuristics. The effectiveness of the dynamic AND/OR approach is demonstrated on a variety of benchmarks for pure 0/1 integer programming, including instances from the MIPLIB library, real-world combinatorial auctions and random uncapacitated warehouse location problems.