Initial application of ant colony optimisation to statistical disclosure control

Serpell, Martin; Smith, Jim

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• Presentation Conference Type: Conference Paper (unpublished)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