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Evolution of the population of a genetic algorithm using particle swarm optimization: application to clustering analysis

Marinakis Ioannis, Marinaki Magdalini, Matsatsinis Nikolaos, Zopounidis, Constantin

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/7462044B-0915-4292-B243-F7DFEFEF1C08-
Αναγνωριστικόhttps://doi.org/10.1007/s12351-008-0029-z-
Γλώσσαen-
Μέγεθος16 pagesen
ΤίτλοςEvolution of the population of a genetic algorithm using particle swarm optimization: application to clustering analysisen
ΔημιουργόςMarinakis Ioannisen
ΔημιουργόςΜαρινακης Ιωαννηςel
ΔημιουργόςMarinaki Magdalinien
ΔημιουργόςΜαρινακη Μαγδαληνηel
ΔημιουργόςMatsatsinis Nikolaosen
ΔημιουργόςΜατσατσινης Νικολαοςel
ΔημιουργόςZopounidis, Constantinen
ΕκδότηςSpringer Verlagen
ΠερίληψηThis 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 PSO. In order to assess the efficacy of the proposed algorithm, this 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%.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-05-
Ημερομηνία Δημοσίευσης2009-
Θεματική ΚατηγορίαClustering analysisen
Βιβλιογραφική ΑναφοράY. Marinakis, M. Marinaki, N. Matsatsinis ,C. Zopounidis, "Evolution of the population of a genetic algorithm using particle swarm optimization: application to clustering analysis," Oper.l Research, vol. 9,no.1 pp. 105-120,Ma. 2009.doi:10.1007/s12351-008-0029-zen

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