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Ottimizzazione numerica

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In questo capitolo presenteremo alcuni fra i più noti metodi numerici per risolvere problemi di ottimizzazione (massimizzazione o minimizzazione) non vincolata. Faremo inoltre qualche cenno alle strategie da utilizzare nel caso dell’ottimizzazione vincolata. Introdurremo i più popolari metodi di discesa, quelli di tipo trust region, i minimi quadrati non lineari, i metodi di Gauss-Newton a quelli di Levenberg-Marquardt, e ne discuteremo le proprietà di convergenza, efficienza e robustezza. Diversi esempi di rilevanza applicativa verranno introdotti all’inizio del capitolo per motivare l’interesse del lettore, mentre numerosi esercizi concluderanno il capitolo.

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Authors and Affiliations

  1. École Polytechnique Fédérale (EPFL), Lausanne, Switzerland

    Alfio Quarteroni

  2. Politecnico di Milano, Milan, Italy

    Alfio Quarteroni

  3. MOX, Politecnico di Milano, Milan, Italy

    Fausto Saleri

  4. DICATAM, Università degli Studi di Brescia, Brescia, Italy

    Paola Gervasio

Authors
  1. Alfio Quarteroni
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  2. Fausto Saleri
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  3. Paola Gervasio
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Quarteroni, A., Saleri, F., Gervasio, P. (2017). Ottimizzazione numerica. In: Calcolo Scientifico. UNITEXT(), vol 105. Springer, Milano. https://doi.org/10.1007/978-88-470-3953-7_7

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