AN EFFICIENT HYBRID METHOD FOR CLUSTERING PROBLEMS

H. Panahi, R. Tavakkoli-Moghaddam

2008

Abstract

This paper presents a hybrid efficient method based on ant colony optimization (ACO) and genetic algorithms (GA) for clustering problems. This proposed method assumes that agents of ACO has life cycle which is variable and changes by a special function. We also apply three local searches on the basis of heuristic rules for the given clustering problem. This proposed method is implemented and tested on two real datasets. Further, its performance is compared with other well-known meta-heuristics, such as ACO, GA, simulated annealing (SA), and tabu search (TS). At last, paired comparison t-test is also applied to proof the efficiency of our proposed method. The associated output gives very encouraging results; however, the proposed method needs longer time to proceed.

Paper Citation

in Harvard Style

Panahi H. and Tavakkoli-Moghaddam R. (2008). AN EFFICIENT HYBRID METHOD FOR CLUSTERING PROBLEMS . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-37-1, pages 288-294. DOI: 10.5220/0001703002880294

in Bibtex Style

@conference{iceis08,
author={H. Panahi and R. Tavakkoli-Moghaddam},
title={AN EFFICIENT HYBRID METHOD FOR CLUSTERING PROBLEMS},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2008},
pages={288-294},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001703002880294},
isbn={978-989-8111-37-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - AN EFFICIENT HYBRID METHOD FOR CLUSTERING PROBLEMS
SN - 978-989-8111-37-1
AU - Panahi H.
AU - Tavakkoli-Moghaddam R.
PY - 2008
SP - 288
EP - 294
DO - 10.5220/0001703002880294