Numerical Nonsmooth Optimization State of the Art Algorithms
Solving nonsmooth optimization (NSO) problems is critical in many practical applications and real-world modeling systems. The aim of this book is to survey various numerical methods for solving NSO problems and to provide an overview of the latest develop
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mooth Optimization State of the Art Algorithms
Numerical Nonsmooth Optimization
Adil M. Bagirov • Manlio Gaudioso • Napsu Karmitsa • Marko M. M¨akel¨a • Sona Taheri Editors
Numerical Nonsmooth Optimization State of the Art Algorithms
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Editors Adil M. Bagirov School of Science, Engineering and Information Technology Federation University Australia Ballarat Victoria, Australia
Manlio Gaudioso Department of Informatics, Modeling, Electronics and System Engineering University of Calabria Rende (CS), Italy
Napsu Karmitsa Department of Mathematics and Statistics University of Turku Turku, Finland
Marko M. M¨akel¨a Department of Mathematics and Statistics University of Turku Turku, Finland
Sona Taheri School of Science, Engineering and Information Technology Federation University Australia Ballarat Victoria, Australia
ISBN 978-3-030-34909-7 ISBN 978-3-030-34910-3 (eBook) https://doi.org/10.1007/978-3-030-34910-3 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Nonsmooth optimization (NSO) refers to the general problem of minimizing (or maximizing) functions that are typically not differentiable at their minimizers (maximizers). This kind of functions can be found in many applications, for instance, in image denoising, optimal control, data mining, economics, computational chemistry, mechanics, engineering, biology, and physics. Since the classical optimization theory presumes certain differentiability and strong regularity assumptions for the functions to be optimized, it cannot be directly utilized, nor can the methods developed for smooth problems. The aim of this book is to give a survey of different numerical methods for solving NSO
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