A Correlation Analysis of Set Quality ...
Type de document :
Communication dans un congrès avec actes
Titre :
A Correlation Analysis of Set Quality Indicator Values in Multiobjective Optimization
Auteur(s) :
Liefooghe, Arnaud [Auteur correspondant]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Derbel, Bilel [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Derbel, Bilel [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Titre de la manifestation scientifique :
Genetic and Evolutionary Computation Conference (GECCO 2016)
Ville :
Denver
Pays :
Etats-Unis d'Amérique
Date de début de la manifestation scientifique :
2016-07-20
Titre de l’ouvrage :
Genetic and Evolutionary Computation Conference (GECCO 2016)
Date de publication :
2016
Mot(s)-clé(s) en anglais :
inverted generational distance
correlation analysis
hypervolume
R-metrics
epsilon indicator
multiobjective optimization
set quality indicators
performance assessment
correlation analysis
hypervolume
R-metrics
epsilon indicator
multiobjective optimization
set quality indicators
performance assessment
Discipline(s) HAL :
Informatique [cs]/Recherche opérationnelle [cs.RO]
Informatique [cs]/Recherche d'information [cs.IR]
Informatique [cs]/Recherche d'information [cs.IR]
Résumé en anglais : [en]
A large spectrum of quality indicators has been proposed so far to assess the performance of discrete Pareto set approximations in multiobjective optimization. Such indicators assign, to any solution set, a real-value ...
Lire la suite >A large spectrum of quality indicators has been proposed so far to assess the performance of discrete Pareto set approximations in multiobjective optimization. Such indicators assign, to any solution set, a real-value reflecting a given aspect of approximation quality. This is an important issue in multiobjective optimization, not only to compare the performance and assets of different approximate algorithms, but also to improve their internal selection mechanisms. In this paper, we adopt a statistical analysis to experimentally investigate by how much a selection of state-of-the-art quality indicators agree with each other for a wide range of Pareto set approximations from well-known two- and three-objective continuous benchmark functions. More particularly, we measure the correlation between the ranking of low-, medium-, and high-quality limited-size approximation sets with respect to inverted generational distance, additive epsilon, multiplicative epsilon, R2, R3, as well as hypervolume indicator values. Since no pair of indicators obtains the same ranking of approximation sets, we confirm that they emphasize different facets of approximation quality. More importantly, our statistical analysis allows the degree of compliance between these indicators to be quantified.Lire moins >
Lire la suite >A large spectrum of quality indicators has been proposed so far to assess the performance of discrete Pareto set approximations in multiobjective optimization. Such indicators assign, to any solution set, a real-value reflecting a given aspect of approximation quality. This is an important issue in multiobjective optimization, not only to compare the performance and assets of different approximate algorithms, but also to improve their internal selection mechanisms. In this paper, we adopt a statistical analysis to experimentally investigate by how much a selection of state-of-the-art quality indicators agree with each other for a wide range of Pareto set approximations from well-known two- and three-objective continuous benchmark functions. More particularly, we measure the correlation between the ranking of low-, medium-, and high-quality limited-size approximation sets with respect to inverted generational distance, additive epsilon, multiplicative epsilon, R2, R3, as well as hypervolume indicator values. Since no pair of indicators obtains the same ranking of approximation sets, we confirm that they emphasize different facets of approximation quality. More importantly, our statistical analysis allows the degree of compliance between these indicators to be quantified.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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- liefooghe.gecco2016.pdf
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