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

Elizabeth Montero, María Cristina Riff

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number6974526
Pages (from-to)3822-3827
Number of pages6
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2014-January
Issue numberJanuary
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States
Duration: 5 Oct 20148 Oct 2014

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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