An Analysis on Selection for High-Resolution Approximations in Many-Objective Optimization

Abstract : This work studies the behavior of three elitist multi- and many-objective evolutionary algorithms generating a high-resolution approximation of the Pareto optimal set. Several search-assessment indicators are defined to trace the dynamics of survival selection and measure the ability to simultaneously keep optimal solutions and discover new ones under different population sizes, set as a fraction of the size of the Pareto optimal set.
Type de document :
Communication dans un congrès
Thomas Bartz-Beielstein; Jürgen Branke; Bogdan Filipič; Jim Smith. Parallel Problem Solving from Nature - PPSN XIII, Sep 2014, Ljubljana, Slovenia. Springer International Publishing, 8672, pp.487-497, 2014, Lecture Notes in Computer Science
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01066206
Contributeur : Sébastien Verel <>
Soumis le : mercredi 24 septembre 2014 - 23:28:52
Dernière modification le : jeudi 21 février 2019 - 10:52:49
Document(s) archivé(s) le : jeudi 25 décembre 2014 - 10:15:42

Fichiers

selection-ppsn14.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01066206, version 1
  • ARXIV : 1409.7478

Citation

Hernan Aguirre, Arnaud Liefooghe, Sébastien Verel, Kiyoshi Tanaka. An Analysis on Selection for High-Resolution Approximations in Many-Objective Optimization. Thomas Bartz-Beielstein; Jürgen Branke; Bogdan Filipič; Jim Smith. Parallel Problem Solving from Nature - PPSN XIII, Sep 2014, Ljubljana, Slovenia. Springer International Publishing, 8672, pp.487-497, 2014, Lecture Notes in Computer Science. 〈hal-01066206〉

Partager

Métriques

Consultations de la notice

635

Téléchargements de fichiers

270