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Pre-processing optimisation applied to the classical integer programming model for statistical disclosure control

Staggemeier, Andrea; Serpell, Martin; Clark, Alistair; Smith, Jim

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Authors

Andrea Staggemeier

Martin Serpell Martin2.Serpell@uwe.ac.uk
Senior Lecturer in Computer Systems and Networks

Alistair Clark

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Jim Smith James.Smith@uwe.ac.uk
Professor in Interactive Artificial Intelligence



Abstract

A pre-processing optimisation is proposed that can be applied to the integer and mixed integer linear programming models that are used to solve the cell suppression problem in statistical disclosure control. In this paper we report our initial findings which confirm that in many situations the pre-processing optimisation can considerably reduce the resources required by the solver hence allowing either statistical tables to be protected quicker, or larger statistical tables to be protected. This pre-processing optimisation may be suitable for application to the τ-Argus Optimal Method used in protecting statistical tables. © 2008 Springer-Verlag Berlin Heidelberg.

Citation

Staggemeier, A., Serpell, M., Clark, A., & Smith, J. (2008). Pre-processing optimisation applied to the classical integer programming model for statistical disclosure control. . https://doi.org/10.1007/978-3-540-87471-3_3

Publication Date Jan 1, 2008
Deposit Date Nov 2, 2010
Publicly Available Date Nov 15, 2016
Publisher Springer Verlag
Volume 5262 LNCS
Pages 24-36
ISBN 9783540874706
DOI https://doi.org/10.1007/978-3-540-87471-3_3
Keywords statistical disclosure control, cell suppression problem, classical model, pre-processing optimisation, external attacker
Public URL https://uwe-repository.worktribe.com/output/1021788
Publisher URL http://dx.doi.org/10.1007/978-3-540-87471-3_3
Related Public URLs http://www.springerlink.com/content/w78205898620h1x2/

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