Evaluating components of artificial immune algorithms: A performance-aware method based on evolutionary calibrator

Elizabeth Montero, María Cristina Riff

Resultado de la investigación: Contribución a una revistaArtículo de la conferencia

1 Cita (Scopus)

Resumen

We are interested in methods and strategies that allow us to simplify bio-inspired algorithms without reducing their accuracy. These algorithms are usually designed and implemented adding new components incrementally which makes inherently difficult to understand the relation between them and their individual contribution to the algorithm performance. In this paper, the information obtained when using a tuner to identify a set of good parameter values is analyzed and a method to use this tuner in order to help us to take design decisions is proposed. Our results are shown and our approach is validated using an artificial immune algorithm which has been proposed to solve multi-objective problems. The results show that these decisions lead to a code that is shorter than that of the initial algorithm while maintaining its performance.

Idioma originalInglés
Número de artículo6974526
Páginas (desde-hasta)3822-3827
Número de páginas6
PublicaciónConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volumen2014-January
N.ºJanuary
DOI
EstadoPublicada - 1 ene 2014
Evento2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, Estados Unidos
Duración: 5 oct 20148 oct 2014

Áreas temáticas de ASJC Scopus

  • Ingeniería eléctrica y electrónica
  • Ingeniería de control y sistemas
  • Interacción persona-ordenador

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