Retroactive ordering for dynamic backtracking

Roie Zivan, Uri Shapen, Moshe Zazone, Amnon Meisels

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Dynamic Backtracking (DBT) is a well known algorithm for solving Constraint Satisfaction Problems. In DBT, variables are allowed to keep their assignment during backjump, if they are compatible with the set of eliminating explanations. A previous study has shown that when DBT is combined with variable ordering heuristics it performs poorly compared to standard Conflict-directed Backjumping (CBJ) [1]. The special feature of DBT, keeping valid elimination explanations during backtracking, can be used for generating a new class of ordering heuristics. In the proposed algorithm, the order of already assigned variables can be changed. Consequently, the new class of algorithms is termed Retroactive DBT. In the proposed algorithm, the newly assigned variable can be moved to a position in front of assigned variables with larger domains and as a result prune the search space more effectively. The experimental results presented in this paper show an advantage of the new class of heuristics and algorithms over standard DBT and over CBJ. All algorithms tested were combined with forward-checking and used a Min-Domain heuristic.

Original languageEnglish
Title of host publicationPrinciples and Practice of Constraint Programming - CP 2006 - 12th International Conference, CP 2006, Proceedings
PublisherSpringer Verlag
Number of pages6
ISBN (Print)3540462678, 9783540462675
StatePublished - 1 Jan 2006
Event12th International Conference on Principles and Practice of Constraint Programming, CP 2006 - Nantes, France
Duration: 25 Sep 200629 Sep 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4204 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Principles and Practice of Constraint Programming, CP 2006

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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