An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems
This paper presents a novel fuzzy clustering technique based on grouping genetic algorithms (GGAs), which are a class of evolutionary algorithms especially modified to tackle grouping problems. Our approach hinges on a GGA devised for fuzzy clustering by means of a novel encoding of individuals (con...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/916371 |
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| author | S. Salcedo-Sanz J. Del Ser Z. W. Geem |
| author_facet | S. Salcedo-Sanz J. Del Ser Z. W. Geem |
| author_sort | S. Salcedo-Sanz |
| collection | DOAJ |
| description | This paper presents a novel fuzzy clustering technique based on grouping genetic algorithms (GGAs), which are a class of evolutionary algorithms especially modified to tackle grouping problems. Our approach hinges on a GGA devised for fuzzy clustering by means of a novel encoding of individuals (containing elements and clusters sections), a new fitness function (a superior modification of the Davies Bouldin index), specially tailored crossover and mutation operators, and the use of a scheme based on a local search and a parallelization process, inspired from an island-based model of evolution. The overall performance of our approach has been assessed over a number of synthetic and real fuzzy clustering problems with different objective functions and distance measures, from which it is concluded that the proposed approach shows excellent performance in all cases. |
| format | Article |
| id | doaj-art-a35b5d0bb0474f8ea51bc7c8bcd2ae80 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-a35b5d0bb0474f8ea51bc7c8bcd2ae802025-02-03T06:13:57ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/916371916371An Island Grouping Genetic Algorithm for Fuzzy Partitioning ProblemsS. Salcedo-Sanz0J. Del Ser1Z. W. Geem2Department of Signal Processing and Communications, Universidad de Alcalá, 28871 Madrid, SpainOPTIMA Area, Tecnalia Research & Innovation, 48170 Bizkaia, SpainDepartment of Energy IT, Gachon University, Seongnam 461-701, Republic of KoreaThis paper presents a novel fuzzy clustering technique based on grouping genetic algorithms (GGAs), which are a class of evolutionary algorithms especially modified to tackle grouping problems. Our approach hinges on a GGA devised for fuzzy clustering by means of a novel encoding of individuals (containing elements and clusters sections), a new fitness function (a superior modification of the Davies Bouldin index), specially tailored crossover and mutation operators, and the use of a scheme based on a local search and a parallelization process, inspired from an island-based model of evolution. The overall performance of our approach has been assessed over a number of synthetic and real fuzzy clustering problems with different objective functions and distance measures, from which it is concluded that the proposed approach shows excellent performance in all cases.http://dx.doi.org/10.1155/2014/916371 |
| spellingShingle | S. Salcedo-Sanz J. Del Ser Z. W. Geem An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems The Scientific World Journal |
| title | An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems |
| title_full | An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems |
| title_fullStr | An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems |
| title_full_unstemmed | An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems |
| title_short | An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems |
| title_sort | island grouping genetic algorithm for fuzzy partitioning problems |
| url | http://dx.doi.org/10.1155/2014/916371 |
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