TOC Front Cover 2 An Algorithmic Approach to Nonlinear Analysis and Optimization 5 Copyright Page 6 Preface 9 Acknowledgments 13 CONTENTS 15 Chapter 1. Iterative Methods on Normed Linear Spaces 19 1.1 Introduction 19 1.2 Contraction Mappings 22 1.3 Differentiation on Normed Spaces 33 1.4 Gradient Techniques 45 1.5 Least Squares Approximation 63 1.6 Two-Point Boundary Value Problems 72 1.7 Further Remarks on Stability 80 Chapter 2. Constrained Optimization on En 85 Front Cover 2 An Algorithmic Approach to Nonlinear Analysis and Optimization 5 Copyright Page 6 Preface 9 Acknowledgments 13 CONTENTS 15 Chapter 1. Iterative Methods on Normed Linear Spaces 19 1.1 Introduction 19 1.2 Contraction Mappings 22 1.3 Differentiation on Normed Spaces 33 1.4 Gradient Techniques 45 1.5 Least Squares Approximation 63 1.6 Two-Point Boundary Value Problems 72 1.7 Further Remarks on Stability 80 Chapter 2. Constrained Optimization on En 85 2.1 Introduction 85 2.2 Semicontinuity and Convexity 86 2.3 A Penalty Argument 96 2.4 The Kuhn–Tucker and Lagrange Multiplier Rules 105 2.5 The Regularity Assumption 116 2.6 Bibliographic Notes and Other Remarks 123 Chapter 3. Computational Techniques for Constrained Optimization on En 128 3.1 Introduction 128 3.2 Implementation of the Penalty Argument 129 3.3 A Conjugate Direction Method 138 3.4 Gradient Projection 150 3.5 Numerical Examples and One-Dimensional Minimization 163 3.6 Bibliographic Notes and Remarks 169 Chapter 4. Constrained Optimization in Function Space 177 4.1 Introduction 177 4.2 Problems of Optimal Control 178 4.3 The Neyman–Pearson Multiplier Rule 189 Chapter 5. Weak Convergence in Hilbert Space 203 5.1 Introduction 203 5.2 Weak Convergence 204 5.3 Fixed Points of Nonexpansive Maps 211 5.4 The Penalty Argument in Hilbert Space 217 5.5 An Existence Question in Optimization 219 Appendix: Computer Program for the Solution of Two-Point Boundary Value Problems 222 Bibliography 247 AUTHOR INDEX 249 SUBJECT INDEX 251 Mathematics in Science and Engineering 254 Show more