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Authors: Yannis Marinakis ; Magdalene Marinaki ; Nikolaos Matsatsinis and Constantin Zopounidis

Affiliation: Technical University of Crete, Greece

Keyword(s): Clustering analysis, Feature selection problem, Memetic Algorithms, Particle Swarm Optimization, GRASP.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Evolutionary Programming ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: This paper presents a new memetic algorithm, which is based on the concepts of Genetic Algorithms (GAs), Particle Swarm Optimization (PSO) and Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm is a two phase algorithm which combines a memetic algorithm for the solution of the feature selection problem and a GRASP algorithm for the solution of the clustering problem. In this paper, contrary to the genetic algorithms, the evolution of each individual of the population is realized with the use of a PSO algorithm where each individual have to improve its physical movement following the basic principles of PSO until it will obtain the requirements to be selected as a parent. Its performance is compared with other popular metaheuristic methods like classic genetic algorithms, tabu search, GRASP, ant colony optimization and particle swarm optimization. In order to assess the efficacy of the proposed algorithm, thi s methodology is evaluated on datasets from the UCI Machine Learning Repository. The high performance of the proposed algorithm is achieved as the algorithm gives very good results and in some instances the percentage of the corrected clustered samples is very high and is larger than 96%. (More)

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Paper citation in several formats:
Marinakis, Y.; Marinaki, M.; Matsatsinis, N. and Zopounidis, C. (2008). A MEMETIC-GRASP ALGORITHM FOR CLUSTERING. In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS; ISBN 978-989-8111-37-1; ISSN 2184-4992, SciTePress, pages 36-43. DOI: 10.5220/0001694700360043

@conference{iceis08,
author={Yannis Marinakis. and Magdalene Marinaki. and Nikolaos Matsatsinis. and Constantin Zopounidis.},
title={A MEMETIC-GRASP ALGORITHM FOR CLUSTERING},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS},
year={2008},
pages={36-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001694700360043},
isbn={978-989-8111-37-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS
TI - A MEMETIC-GRASP ALGORITHM FOR CLUSTERING
SN - 978-989-8111-37-1
IS - 2184-4992
AU - Marinakis, Y.
AU - Marinaki, M.
AU - Matsatsinis, N.
AU - Zopounidis, C.
PY - 2008
SP - 36
EP - 43
DO - 10.5220/0001694700360043
PB - SciTePress