An ant colony approach for clustering

By Prakash Shelokar, V. Jayaraman, B. D. Kulkarni. 2004

551 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Hybrid clustering analysis using improved krill herd algorithm (2018, methodology): “Ant Colony optimization (ACO) algorithm is a probabilistic technique that is used to find good paths.”
An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis (2010, methodology): “[8] presented an ant colony optimization, methodology for optimally clustering N objects into K clusters.”
A Comprehensive Survey of Clustering Algorithms (2015, background): “For more detailed information about this kind of clustering algorithms, you can refer to [102–104].”
An artificial bee colony approach for clustering (2010, methodology): “An ant colony clustering algorithm for clustering is presented by Shelokar, Jayaraman, and Kulkarni (2004).”
A survey on nature inspired metaheuristic algorithms for partitional clustering (2014, methodology): “gence algorithms like ant colony optimization [183] and particle swarm optimization [219] have been applied for cluster analysis.”