The optimization of multi objective problems is currently an area of important research and development. The importance of type of problems has allowed the development of multiple metaheuristics for their solution. To determine which multi objective metaheuristic has the best performance with respect to a problem, in this article an experimental comparison between two of them: Sorting Genetic Algorithm No dominated-II (NSGA-II) and Multi Objective Particle Swarm Optimization (MOPS) using ZDT test functions is made. The results obtained by both algorithms are compared and analyzed based on different performance metrics that evaluate both the dispersion of the solutions on the Pareto front, and its proximity to it.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Experimental Comparison of Multiobjective Algorithms: NSGA-II and OMOPSO




    Erscheinungsdatum :

    01.09.2010


    Format / Umfang :

    352562 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Multiobjective Optimization design of high frequency transformer based on NSGA-II algorithm

    Wang, Chunjie / Han, Wenkai / Chen, Peng et al. | British Library Conference Proceedings | 2022



    Tuning of Two-Degrees-of-Freedom PID Controllers via the Multiobjective Genetic Algorithm NSGA-II

    Lagunas-Jimenez, Ruben / Fernandez-Anaya, Guillermo / Martinez-garcia, J. | IEEE | 2006


    Comparison between Multiobjective Population-Based Algorithms in Mechanical Problem

    Radhi, H.E. / Barrans, S.M. | British Library Conference Proceedings | 2012


    NSGA-III_01.json

    Zorn, Max Benjamin / Claus, Luisa / Frenzel, Christian et al. | DataCite | 2024