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An Empirical Comparison of Backtracking Algorithms

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2 Author(s)
Cynthia A. Brown ; Department of Computer Science, Indiana University, Bloomington, IN 47405. ; Paul W. Purdom

In this paper we report the results of experimental studies of zero-level, one-level, and two-level search rearrangement backtracking. We establish upper and lower limits for the size problem for which one-level backtracking is preferred over zero-level and two-level methods, thereby showing that the zero-level method is best for very small problems. The one-level method is best for moderate size problems, and the two-level method is best for extremely large problems. Together with our theoretical asymptotic formulas, these measurements provide a useful guide for selecting the best search rearrangement method for a particular problem.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:PAMI-4 ,  Issue: 3 )