International Conference on Logic Programming and Nonmonotonic Reasoning

LPNMR 2015: Logic Programming and Nonmonotonic Reasoning pp 213-227

Efficient Problem Solving on Tree Decompositions Using Binary Decision Diagrams

Conference paper

DOI: 10.1007/978-3-319-23264-5_19

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9345)
Cite this paper as:
Charwat G., Woltran S. (2015) Efficient Problem Solving on Tree Decompositions Using Binary Decision Diagrams. In: Calimeri F., Ianni G., Truszczynski M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2015. Lecture Notes in Computer Science, vol 9345. Springer, Cham


Dynamic programming (DP) on tree decompositions is a well studied approach for solving hard problems efficiently. Usually, implementations rely on tables for storing information, and algorithms specify how tuples are manipulated during traversal of the decomposition. However, a bottleneck of such table-based algorithms is relatively high memory consumption. Binary Decision Diagrams (BDDs) and related concepts have been shown to be very well suited to store information efficiently. While several techniques have been proposed that combine DP with efficient BDD-based storage for some particular problems, in this work we present a general approach where DP algorithms are specified on a logical level in form of set-based formula manipulation operations that are executed directly on the BDD data structure. In the paper, we provide several case studies in order to illustrate the method at work, and report on preliminary experiments. These show promising results, both with respect to memory and run-time.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institute of Information SystemsTU WienWienAustria

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