Nonlinear Optimization
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Beschreibung
This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences. Organized into two parts, this book may be used as a primary text for courses on convex optimization and non-convex optimization. Definitions, proofs, and numerical methods are well illustrated and all chapters contain compelling exercises. The exercises emphasize fundamental theoretical results on optimality and duality theorems, numerical methods with or without constraints, and derivative-free optimization. Selected solutions are given. Applications to theoretical results and numerical methods are highlighted to help students comprehend methods and techniques.
This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences. Organized into two parts, this book may be used as a primary text for courses on convex optimization and non-convex optimization. Definitions, proofs, and numerical methods are well illustrated and all chapters contain compelling exercises. The exercises emphasize fundamental theoretical results on optimality and duality theorems, numerical methods with or without constraints, and derivative-free optimization. Selected solutions are given. Applications to theoretical results and numerical methods are highlighted to help students comprehend methods and techniques.
Textbook for convex optimization and non-convex optimization courses Contains exercises with select solutions Features model building, real problems, and applications of optimization models Provides numerical approaches to solve nonlinear optimization problems
Autor*in
Francisco J. Aragón
Themen in »Nonlinear Optimization«
convexity coercivity linear regression Jensen's inequalities polynomial regression Lagrange duality Nelder and Mead method Fermat-Steiner problem Quasi-Newton methods optimization problems unconstrained optimization geometric optimizqtion quadratic optimiztion wolfe duality optimization algorithms
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“The book can be used for ‘upper-level undergraduate students of mathematics and statistics, and graduate students of industrial engineering.’ … I would recommend it to students for further reading and to colleagues for its nicely illustrated material that may be used for designing their lectures on nonlinear optimization.” (Martin Schmidt, SIAM Review, Vol. 62 (2), 2020)
“This book is a valuable contribution to optimization, its theory, methods and applications ... . Applications to theoretical results and numerical methods are highlighted to help readers, e.g., students, in order to understand and learn approaches and methods. This excellent book is clearly and well structured, analytically deep, well exemplified, beautifully illustrated, and written with care and taste.” (Gerhard-Wilhelm, WeberJoanna Majchrzak and Erik Kropat, zbMATH 1423.90001, 2019)
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