Isbn: 9781332868841 - implementation of the schnabel and eskow modified cholesky factorization in the context of a truncated-newton optimization method (classic reprint) (3 risultati)

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  • Lingua: Inglese

    Editore: Forgotten Books, 2018

    1332868843 / 9781332868841

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    Condizione: Nuovo

    EUR 24,77

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    Quantità: 15 disponibili

    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

  • Lingua: Inglese

    Editore: Forgotten Books, 2018

    1332868843 / 9781332868841

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    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    Condizione: Nuovo

    EUR 24,51

    EUR 3,84 spedizione 
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    Quantità: 15 disponibili

    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

  • Lingua: Inglese

    Editore: Forgotten Books, 2024

    1332868843 / 9781332868841

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    • Print on Demand

    Da: Forgotten Books, London, Regno UnitoForgotten Books

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    EUR 15,67

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    Paperback. Condizione: New. Print on Demand. This book delves into the fascinating world of nonlinear optimization, a field that seeks to find the best solutions to complex problems where the relationships between variables are not simple. The author specifically focuses on a technique known as the Modified Cholesky Factorization (MCF), a powerful tool for solving large, sparse systems of equations that arise in various scientific disciplines. The book compares two popular MCF implementations: the Gill, Murray, and Wright (GMW) method and the Schnabel & Eskow (S&E) method. While both factorizations have been widely used in the context of nonlinear optimization, this book explores their differences in performance and highlights how the S&E method may be particularly advantageous for dealing with highly indefinite systems, those that exhibit a complex combination of positive and negative values. The book analyzes various numerical experiments to demonstrate how each approach tackles the challenges of finding solutions for different types of problems, and concludes with a compelling argument for the S&E method as a potentially more efficient and robust tool for solving the types of complex equations that arise in fields like computational chemistry and mathematical biology. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item.