Result: Illustration of fairness in evolutionary multi-objective optimization

Title:
Illustration of fairness in evolutionary multi-objective optimization
Authors:
FRIEDRICH, Tobias, HOROBA, Christian, NEUMANN, Frank
Source:
Theoretical computer science. 412(17):1546-1556
Publisher Information:
Oxford: Elsevier, 2011.
Publication Year:
2011
Physical Description:
print, 23 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Optimisation et calcul variationnel numériques, Numerical methods in optimization and calculus of variations, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Divers, Miscellaneous, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Analyse temporelle, Time analysis, Análisis temporal, Comportement, Behavior, Conducta, Informatique théorique, Computer theory, Informática teórica, Méthode optimisation, Optimization method, Método optimización, Optimisation, Optimization, Optimización, 49XX, 58A25, 65K10, 65Kxx, 68Wxx, Equité, Evolutionary algorithms, Fairness, Multi-objective optimization, Running time analysis, Theory
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Mox-Planck-Institut für Informatik, 66123, Saarbrücken, Germany
Fakultät für Informatik, LS 2, TU Dortmund, 44221 Dortmund, Germany
ISSN:
0304-3975
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=23942155
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Mathematics
Accession Number:
edscal.23942155
Database:
PASCAL Archive

Further Information

It is widely assumed that evolutionary algorithms for multi-objective optimization problems should use certain mechanisms to achieve a good spread over the Pareto front. In this paper, we examine such mechanisms from a theoretical point of view and analyze simple algorithms incorporating the concept of fairness. This mechanism tries to balance the number of offspring of all individuals in the current population. We rigorously analyze the runtime behavior of different fairness mechanisms and present illustrative examples to point out situations, where the right mechanism can speed up the optimization process significantly. We also indicate drawbacks for the use of fairness by presenting instances, where the optimization process is slowed down drastically.