Abstract
We consider the longest common subsequence (LCS) problem and propose a new method for obtaining tight upper bounds on the solution length. Our method relies on the compilation of a relaxed multi-valued decision diagram (MDD) in a special way that is based on the principles of A\(^*\) search. An extensive experimental evaluation on several standard LCS benchmark instance sets shows that the novel construction algorithm clearly outperforms a traditional top-down construction (TDC) of MDDs. We are able to obtain stronger and at the same time more compact relaxed MDDs than TDC and this in shorter time. For several groups of benchmark instances new best known upper bounds are obtained. In comparison to existing simple upper bound procedures, the obtained bounds are on average 14.8% better.
This project is partially funded by the Doctoral Program “Vienna Graduate School on Computational Optimization”, Austrian Science Foundation (FWF) Project No. W1260-N35.
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Horn, M., Raidl, G.R. (2021). A\(^*\)-Based Compilation of Relaxed Decision Diagrams for the Longest Common Subsequence Problem. In: Stuckey, P.J. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2021. Lecture Notes in Computer Science(), vol 12735. Springer, Cham. https://doi.org/10.1007/978-3-030-78230-6_5
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