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The use of fuzzy connectives to design real-coded genetic algorithms
dc.contributor.author | Herrera Triguero, Francisco |
dc.contributor.author | Lozano, M. |
dc.contributor.author | Verdegay, José Luis |
dc.date.accessioned | 2007-03-05T17:24:14Z |
dc.date.available | 2007-03-05T17:24:14Z |
dc.date.issued | 1994 |
dc.identifier.issn | 1134-5632 |
dc.identifier.uri | http://hdl.handle.net/2099/2453 |
dc.description.abstract | Genetic algorithms are adaptive methods that use principles inspired by natural population genetics to evolve solutions to search and optimization problems. Genetic algorithms process a population of search space solutions with three operations: selection, crossover and mutation. A great problem in the use of genetic algorithms is premature convergence; the search becomes trapped in a local optimum before the global optimum is found. Fuzzy logic techniques may be used for solving this problem. This paper presents one of them: the design of crossover operators for real-coded genetic algorithms using fuzzy connectives and its extension based on the use of parameterized fuzzy connectives as tools for tackling the premature convergence problem. |
dc.format.extent | 11 |
dc.language.iso | eng |
dc.publisher | Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica |
dc.relation.ispartof | Mathware & soft computing . 1994 Vol. 1 Núm. 3 p.239-251 |
dc.rights | Reconeixement-NoComercial-CompartirIgual 3.0 Espanya |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject.other | Genetic Algorithms |
dc.subject.other | Real Coding |
dc.subject.other | Fuzzy Connectives |
dc.title | The use of fuzzy connectives to design real-coded genetic algorithms |
dc.type | Article |
dc.subject.lemac | Algorismes genètics |
dc.subject.ams | Classificació AMS::03 Mathematical logic and foundations::03E Set theory |
dc.rights.access | Open Access |
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1994, Vol. I, Núm. 3 [13]
ESTYLF'94