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Article

Evolutionary multi-objective optimization: basic concepts and some applications in pattern recognition

Author:

Carlos A. Coello CoelloAuthors Info & Claims

MCPR'11: Proceedings of the Third Mexican conference on Pattern recognition

Pages 22 - 33

Published: 29 June 2011 Publication History

Abstract

This paper provides a brief introduction to the so-called multi-objective evolutionary algorithms, which are bio-inspired metaheuristics designed to deal with problems having two or more (normally conflicting) objectives. First, we provide some basic concepts related to multi-objective optimization and a brief review of approaches available in the specialized literature. Then, we provide a short review of applications of multi-objective evolutionary algorithms in pattern recognition. In the final part of the paper, we provide some possible paths for future research in this area, which are promising, from the author's perspective.

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Cited By

Ye QPan HLiu C(2015)Enhancement of ELM by clustering discrimination manifold regularization and multiobjective FOA for semisupervised classificationComputational Intelligence and Neuroscience10.1155/2015/7314942015(51-51)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2015/731494
Reynoso-Meza GSanchis JBlasco XGarcía-Nieto S(2014)Physical programming for preference driven evolutionary multi-objective optimizationApplied Soft Computing10.1016/j.asoc.2014.07.00924:C(341-362)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1016/j.asoc.2014.07.009

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Information & Contributors

Information

Published In

cover image Guide Proceedings

MCPR'11: Proceedings of the Third Mexican conference on Pattern recognition

June 2011

349 pages

ISBN:9783642215865

Editors:
José Francisco Martínez-Trinidad
National Institute of Astrophysics, Optics and Electronics, Computer Science Department, Puebla, Mexico
,
Jesús Ariel Carrasco-Ochoa
National Institute of Astrophysics, Optics and Electronics, Computer Science Department, Puebla, Mexico
,
Cherif Ben-Youssef Brants
Cancun Technological Institute, Quintana Roo, Mexico
,
Edwin Robert Hancock
University ofYork, Department of Computer Science, York, UK

Sponsors

Cancun Technological Institute: Cancun Technological Institute
Mexican Association for Computer Vision, Neurocomputing and Robotics: Mexican Association for Computer Vision, Neurocomputing and Robotics
National Institute of Astrophysics: National Institute of Astrophysics, Optics and Electronics
IAPR: International Association for Pattern Recognition

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 29 June 2011

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Cited By

Ye QPan HLiu C(2015)Enhancement of ELM by clustering discrimination manifold regularization and multiobjective FOA for semisupervised classificationComputational Intelligence and Neuroscience10.1155/2015/7314942015(51-51)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2015/731494
Reynoso-Meza GSanchis JBlasco XGarcía-Nieto S(2014)Physical programming for preference driven evolutionary multi-objective optimizationApplied Soft Computing10.1016/j.asoc.2014.07.00924:C(341-362)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1016/j.asoc.2014.07.009

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