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SOURCE: Galewski M. Basics of Nonlinear Optimization.Around the Weierstrass Theorem 2024
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COVER

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MEDIAINFO
Textbook in PDF format
This textbook gives an introduction to optimization tools which arise around the Weierstrass theorem about the minimum of a lower semicontinuous function. Starting from a Euclidean space, it moves further into the infinite dimensional setting towards the direct variational method, going through differentiation and introducing relevant background information on the way.
Exercises accompany the text and include observations, remarks, and examples that help understand the presented material. Although some basic knowledge of functional analysis is assumed, covering Hilbert and Banach spaces and the Lebesgue integration, the required background material is covered throughout the text, and literature suggestions are provided. For less experienced readers, a summary of some optimization techniques is also included.
The book will appeal to both students and instructors in specialized courses on optimization, wishing to learn more about variational methods.
Preface
The Weierstrass Theorem the Origin of Optimization
Introductory Remarks
Lower Semicontinuity and the Weierstrass Theorem
Applications to Minimization Problems
Applications to Global Invertibility
Applications to Algebraic Equations
The Lagrange Multiplier Rule
Some Basics from Functional Analysis and Function Spaces
On the Convexity with Some Revision from the Calculus
On the Weak Convergence
Niemytskij Operator and the Krasnosel'skii-Type Theorem
On the Space C[0,1]
On Absolutely Continuous Functions
On the Spaces H1(0,1) and H01(0,1)
Definition and Basic Properties
Embeddings of the Space H01(0,1)
The Space H-1(0,1)
On the du Bois-Reymond Lemma and the Regularity Results
Differentiation in Infinite-Dimensional Spaces
The Gâteaux Variation and Its Computation
On the Fermat Rule
The Gâteaux Derivative
The Fréchet Derivative
On the Differentiability of Maps Between Banach Spaces
More on the Convexity
On the Weierstrass Theorem in Infinite-Dimensional Spaces
Direct Variational Method
Some Remarks on Approximation Problems
Minimization of the Classical Euler Action Functional
Applications to Control Problems
Applications to Second-Order Dirichlet Problems
On the Best Constant in the Poincaré Inequality
On Some Abstract Formulation of the Direct Method
Applications to Multiple Integrals
Instead of an Introduction
On the Space C( Ω)
Sobolev Spaces
Some Applications to Integral Functionals
On the Dirichlet Problem
References
Index
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