Strong valid inequalities for Boolean logical pattern generation

Kedong Yan () and Hong Seo Ryoo ()
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Kedong Yan: Korea University
Hong Seo Ryoo: Korea University

Journal of Global Optimization, 2017, vol. 69, issue 1, No 9, 183-230

Abstract: Abstract 0–1 multilinear programming (MP) captures the essence of pattern generation in logical analysis of data (LAD). This paper utilizes graph theoretic analysis of data to discover useful neighborhood properties among data for data reduction and multi-term linearization of the common constraint of an MP pattern generation model in a small number of stronger valid inequalities. This means that, with a systematic way to more efficiently generating Boolean logical patterns, LAD can be used for more effective analysis of data in practice. Mathematical properties and the utility of the new valid inequalities are illustrated on small examples and demonstrated through extensive experiments on 12 real-life data mining datasets.

Keywords: Boolean logic; Logical analysis of data; Pattern; 0–1 multilinear programming; 0–1 linearization; Hypercube; Clique (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10898-017-0512-2

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