This chapter describes the differences between single-objective, multi-objective, and many-objective optimization problems. In multi- and many-objective optimization, often the objectives are conflicting; hence there is no single best point, and a trade-off between the objectives must be considered. Many-objective optimization problems can be more difficult than multi-objective problems mainly because of the curse of dimensionality and because it is also difficult to visualize the trade-off between the objectives. To solve many-objective optimization problems, some algorithms are designed with the challenges in consideration. These algorithms are also described in this chapter, including surrogate-assisted algorithms. Furthermore, several benchmark problems to test and compare the algorithms are discussed.


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    Titel :

    An Introduction to Many-Objective Evolutionary Optimization


    Beteiligte:
    Vasile, Massimiliano (Herausgeber:in) / Irawan, Dani (Autor:in) / Naujoks, Boris (Autor:in)


    Erscheinungsdatum :

    10.09.2020


    Format / Umfang :

    37 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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