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International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research

CPAIOR 2018: Integration of Constraint Programming, Artificial Intelligence, and Operations Research pp 198–214Cite as

From Backdoor Key to Backdoor Completability: Improving a Known Measure of Hardness for the Satisfiable CSP

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 10848)

Abstract

Many studies have been conducted on the complexity of Constraint Satisfaction Problem (CSP) classes. However, there exists little theoretical work on the hardness of individual CSP instances. In this context, the backdoor key fraction (BKF) [17] was introduced as a quantifier of problem hardness for individual satisfiable instances with regard to backtracking search. In our paper, after highlighting the weaknesses of the BKF, we propose a better characterization of the hardness of an individual satisfiable CSP instance based on the ratio between the size of the solution space and that of the search space. We formally show that our measure is negatively correlated with instance hardness. We also show through experiments that this measure evaluates more accurately the hardness of individual instances than the BKF.

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Acknowledgements

This research has been funded by Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289.

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Authors and Affiliations

  1. Insight Centre for Data Analytics, Department of Computer Science, University College Cork, Cork, Ireland

    Guillaume Escamocher, Mohamed Siala & Barry O’Sullivan

Authors
  1. Guillaume Escamocher
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  2. Mohamed Siala
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  3. Barry O’Sullivan
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Corresponding author

Correspondence to Mohamed Siala .

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Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Willem-Jan van Hoeve

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Escamocher, G., Siala, M., O’Sullivan, B. (2018). From Backdoor Key to Backdoor Completability: Improving a Known Measure of Hardness for the Satisfiable CSP. In: van Hoeve, WJ. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2018. Lecture Notes in Computer Science(), vol 10848. Springer, Cham. https://doi.org/10.1007/978-3-319-93031-2_14

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  • DOI: https://doi.org/10.1007/978-3-319-93031-2_14

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