Introduction to nonlinear and global optimization

This self-contained text provides a solid introduction to global and nonlinear optimization, providing students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. The book offers a unique hands-on and critical approach to applied optimization w...

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Bibliographic Details
Main Authors: Hendrix, Eligius M. T., Tóth, Boglárka (Author)
Format: Livre numérique
Language:Anglais
Published: New York, NY : Springer New York [20..].
Cham : Springer Nature
Series:Springer Optimization and Its Applications 37
Online Access:Accès sur la plateforme de l'éditeur
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Accès Université d'Orléans
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Note: Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Introduction to nonlinear and global optimization, by Eligius M.T. Hendrix,... Boglárka G.-Tóth,..., New York, Springer, 2010, 1 vol. (XI-208 p.), Springer optimization and its applications, 978-0-387-88669-5
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505 1 |a Mathematical modeling, cases NLP optimality conditions Goodness of optimization algorithms Nonlinear Programming algorithms Deterministic GO algorithms Stochastic GO algorithms 
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520 |a This self-contained text provides a solid introduction to global and nonlinear optimization, providing students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. The book offers a unique hands-on and critical approach to applied optimization which includes the presentation of numerous algorithms, examples, and illustrations, designed to improve the reader s intuition and develop the analytical skills needed to identify optimization problems, classify the structure of a model, and determine whether a solution fulfills optimality conditions. Key features of "Introduction to Nonlinear and Global Optimization": - Offers insights into relevant concepts such as "regions of attraction", "branch-and-bound", and "cross-cutting" methods as well as many other useful methodologies. -Exhibits numerical examples and exercises developing the reader s familiarity with the terminology and algorithms that are frequently encountered in scientific literature. - Presents various heuristic and stochastic optimization techniques demonstrating how each be applied to a variety of models from biology, engineering, finance, chemistry, and economics. This book is intended to serve as a primary text in an advanced undergraduate or graduate course focusing on nonlinear and global optimization and requires an understanding of basic calculus and linear algebra 
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