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Practical optimization : algorithms and engineering applications

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Cover of 'Practical optimization : algorithms and engineering applications'

Table of Contents

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    Book Overview
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    Chapter 1 The Optimization Problem
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    Chapter 2 Basic Principles
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    Chapter 3 General Properties of Algorithms
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    Chapter 4 One-Dimensional Optimization
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    Chapter 5 Basic Multidimensional Gradient Methods
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    Chapter 6 Conjugate-Direction Methods
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    Chapter 7 Quasi-Newton Methods
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    Chapter 8 Minimax Methods
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    Chapter 9 Applications of Unconstrained Optimization
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    Chapter 10 Fundamentals of Constrained Optimization
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    Chapter 11 Linear Programming Part I: The Simplex Method
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    Chapter 12 Linear Programming Part II: Interior-Point Methods
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    Chapter 13 Quadratic and Convex Programming
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    Chapter 14 Semidefinite and Second-Order Cone Programming
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    Chapter 15 General Nonlinear Optimization Problems
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    Chapter 16 Applications of Constrained Optimization
Attention for Chapter 11: Linear Programming Part I: The Simplex Method
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