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

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

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.

• Presentation Conference Type: Conference Paper (published)
• 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/