High performance architecture for NSGA-II

Josué Domínguez, Oscar Montiel, Roberto Sepúlveda, Nataly Medina

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

Abstract

NSGA-II is one of the most popular algorithms for solving Multiobjective Optimization Problems. It has been used to solve different real-world optimization problems. However, NSGA-II has been criticized for its high computational cost and bad performance on applications with more than two objective functions. In this paper, we propose a high performance architecture for the NSGA-II using parallel computing, for evaluation functions and genetic operators. In the proposed architecture, the Mishra Fast Algorithm for finding the Non Dominated Set was used. We present results for five different test functions.

Original languageEnglish
Title of host publicationRecent Advances on Hybrid Intelligent Systems
EditorsOscar Castillo, Patricia Melin, Oscar Castillo, Patricia Melin, Janusz Kacprzyk
Pages451-461
Number of pages11
DOIs
StatePublished - 2013

Publication series

NameStudies in Computational Intelligence
Volume451
ISSN (Print)1860-949X

Keywords

  • GA
  • NSGA
  • NSGA - II

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