Practical Mathematical Optimization Basic Optimization Theory and Gr
This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are present
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Jan A. Snyman Daniel N. Wilke
Practical Mathematical Optimization Basic Optimization Theory and Gradient-Based Algorithms Second Edition
Springer Optimization and Its Applications VOLUME 133 Managing Editor Panos M. Pardalos (University of Florida) Editor–Combinatorial Optimization Ding-Zhu Du (University of Texas at Dallas) Advisory Board J. Birge (University of Chicago) S. Butenko (Texas A & M University) S. Rebennack (Karlsruhe Institute of Technology) F. Giannessi (University of Pisa) T. Terlaky (Lehigh University) Y. Ye (Stanford University)
Aims and Scope Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics, engineering, medicine, economics and other sciences. The series Springer Optimization and Its Applications publishes undergraduate and graduate textbooks, monographs and state-of-the-art expository works that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization (convex and nonconvex), network flow problems, stochastic optimization, optimal control, discrete optimization, multi-objective programming, description of software packages, approximation techniques and heuristic approaches.
More information about this series at http://www.springer.com/series/7393
Jan A. Snyman · Daniel N. Wilke
Practical Mathematical Optimization Basic Optimization Theory and Gradient-Based Algorithms Second Edition
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Jan A. Snyman Department of Mechanical and Aeronautical Engineering University of Pretoria Pretoria South Africa
Daniel N. Wilke Department of Mechanical and Aeronautical Engineering University of Pretoria Pretoria South Africa
Additional material to this book can be downloaded from http://extras.springer.com. ISSN 1931-6828 ISSN 1931-6836 (electronic) Springer Optimization and Its Applications ISBN 978-3-319-77585-2 ISBN 978-3-319-77586-9 (eBook) https://doi.org/10.1007/978-3-319-77586-9 Library of Congress Control Number: 2018935221 Mathematics Subject Classification (2010): 65K05, 90C30, 90C26, 90C59 1st edition: © Springer Science+Business Media, Inc. 2005 2nd edition: © Springer International Publishing AG, part of Springer Nature 2018 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,
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