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Título del libro: Proceedings Of The 12th Annual Genetic And Evolutionary Computation Conference, Gecco '10
Título del capítulo: Amount and type of information: A GA-Hardness taxonomy

Autores UNAM:
JUAN ARTURO HERRERA ORTIZ; CARLOS OLIVER MORALES; KATYA RODRIGUEZ VAZQUEZ;
Autores externos:

Idioma:
Inglés
Año de publicación:
2010
Palabras clave:

Empirical studies; Problem difficulty; Genetic algorithms; Taxonomies; Hardness


Resumen:

In literature, GA hardness has been studied as the product of only one source or several quasi separable sources; however none of such approaches has been successful. In addition, several hardness models have been conceived in order to analyze, quantify and/or predict difficulty, despite most of them are not able to describe hardness in a suitable way. How hardness is affected by the amount and type of information inherent to the problem seems to be a promising perspective. This work, is then a preliminary empirical study that proposes hardness taxonomy to classify problems using a combination of two broad-spectrum sources: amount and type of information.


Entidades citadas de la UNAM: