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AAAI 1996

Improved Limited Discrepancy Search

Conference Paper Search Control Artificial Intelligence

Abstract

We present an improvement to Harvey and Ginsberg’s limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from the root to the maximum search depth only once. For a complete binary tree of depth d, this reduces the asymptotic complexity from O((d+2/2)(2^d)) to O(2^d). The savings is much less in a partial tree search, or in a heavily pruned tree. The overhead of the improved algorithm on a complete b-ary tree is only a factor of b/(b - 1) compared to depth-first search. While this constant factor is greater on a heavily pruned tree, this improvement makes limited discrepancy search a viable alternative to depth-first search, whenever the entire tree may not be searched. Finally, we present both positive and negative empirical results on the utility of limited discrepancy search, for the problem of number partitioning.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
203521585415003029