A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM
In this paper we consider the problem of clustering m objects into c clusters. The objects are represented by points in an n-dimensional Euclidean space, and the objective is to classify these m points into c clusters such that the distance between points within a cluster and its center (which is to...
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2020
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| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/2549/1/a_tabu_search_approach_to_the_clustering_alsultan_isi_a1995rv43600011.pdf |
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| _version_ | 1864513401247498240 |
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| author | AlSultan, K.S. |
| author2 | unknown |
| author2_role | author |
| author_facet | AlSultan, K.S. unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | AlSultan, K.S. unknown |
| dc.date.*.fl_str_mv | 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/2549/1/a_tabu_search_approach_to_the_clustering_alsultan_isi_a1995rv43600011.pdf A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM. PATTERN RECOGNITION, 28. pp. 1443-1451. |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | PERGAMON-ELSEVIER SCIENCE LTD |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/2549/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | In this paper we consider the problem of clustering m objects into c clusters. The objects are represented by points in an n-dimensional Euclidean space, and the objective is to classify these m points into c clusters such that the distance between points within a cluster and its center (which is to be found) is minimized. The problem is a nonconvex program that has many local minima. It has been studied by many researchers and the most well-known algorithm for solving it is the k-means algorithm. In this paper, we develop a new algorithm for solving this problem based on a tabu search technique. Preliminary computational experience on the developed algorithm are encouraging and compare favorably with both the k-means and the simulated annealing algorithms. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_eee1ba398475621b190f1a9ef30e986a |
| identifier_str_mv | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM. PATTERN RECOGNITION, 28. pp. 1443-1451. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::2549 |
| publishDate | 2020 |
| publisher.none.fl_str_mv | PERGAMON-ELSEVIER SCIENCE LTD |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEMAlSultan, K.S.unknownComputerIn this paper we consider the problem of clustering m objects into c clusters. The objects are represented by points in an n-dimensional Euclidean space, and the objective is to classify these m points into c clusters such that the distance between points within a cluster and its center (which is to be found) is minimized. The problem is a nonconvex program that has many local minima. It has been studied by many researchers and the most well-known algorithm for solving it is the k-means algorithm. In this paper, we develop a new algorithm for solving this problem based on a tabu search technique. Preliminary computational experience on the developed algorithm are encouraging and compare favorably with both the k-means and the simulated annealing algorithms.PERGAMON-ELSEVIER SCIENCE LTDArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/2549/1/a_tabu_search_approach_to_the_clustering_alsultan_isi_a1995rv43600011.pdf A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM. PATTERN RECOGNITION, 28. pp. 1443-1451. enhttps://eprints.kfupm.edu.sa/id/eprint/2549/2020info:eu-repo/semantics/openAccessoai::25492019-11-01T13:44:46Z |
| spellingShingle | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM AlSultan, K.S. Computer |
| status_str | publishedVersion |
| title | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| title_full | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| title_fullStr | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| title_full_unstemmed | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| title_short | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| title_sort | A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/2549/1/a_tabu_search_approach_to_the_clustering_alsultan_isi_a1995rv43600011.pdf |