Skip to main content

Research Repository

Advanced Search

Initial application of ant colony optimisation to statistical disclosure control

Serpell, Martin; Smith, Jim

Authors

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

Profile image of Jim Smith

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



Abstract

In this paper Ant Colony Optimisation (ACO) is applied in the field of Statistical Disclosure Control (SDC) for the first time. It has been applied to a permutation problem found in Cell Suppression. ACO has successfully improved the suppression patterns created to protect published statistical tables but when compared to using the Genetic Algorithm (GA) it has not performed as well. It has however performed well enough to merit further investigation into its use in SDC. In particular research into how to construct a distance matrix for the Cell Suppression Problem (CSP) may both improve the performance of ACO when it is applied in that field and provide further insight into SDC.

Presentation Conference Type Conference Paper (unpublished)
Conference Name Fifteenth annual conference on Genetic and evolutionary computation
Start Date Jul 7, 2013
End Date Jul 9, 2013
Publication Date Jul 1, 2013
Peer Reviewed Peer Reviewed
Pages 97-104
Keywords ant colony algorithm, swarm intelligence, statistical disclosure control
Public URL https://uwe-repository.worktribe.com/output/930569
Publisher URL http://dl.acm.org/citation.cfm?id=2463386
Additional Information Title of Conference or Conference Proceedings : GECCO '13 Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference