A bi-tour ant colony optimisation framework for vertical partitions. (1st January 2011)

• Record Type: Journal Article
• Authors: Cheng, Chun-Hung; Gunasekaran, Angappa; Woo, Kwan-Ho
• Is Part Of: International journal of industrial and systems engineering. Volume 7:Number 3(2011)
• Page Start: 341
• Page End: 356
• Publication Date: 2011-01-01
• Subjects: block clustering -- ACO -- ant colony optimisation -- vertical partitioning; Systems engineering -- Periodicals; Industrial engineering -- Periodicals; 620.001171
• DOI: 10.1504/IJISE.2011.038983
• Languages: English
• ISSNs: 1748-5037

Abstract

Clustering refers to a process of grouping together similar objects while separating out the dissimilar objects. In this work, we consider block clustering in vertical partitioning. Block clustering is a specific clustering method, which clusters the sets of objects and their associated attributes (descriptors) together, simultaneously, in a solution matrix. For this specific problem we propose using a bi-tour ant colony optimisation. To show the quality of the new proposed approach, we conduct an extensive computational study and show that our method is performed better than some traditional clustering methods, such as genetic algorithms and average linkage clustering.