目录 Preface prefcetothe Second Edition 1 Introduction Mathematical Formulation Example:A Transportation Problem Continuous versus Discrete Optimization Constrained and Unconstrained Optimization Global and Local Optimization Stocbastic and Deterministic Optimization Convexity Optimization Algorithms Notes and References 2 Fundamentals of Unconstrained Optimization 2.1 What ls a Solution? Recognizing a Local Minimum Nonsmooth Problems 2.2 Overview of A1gorithms Two Strategies:Line Search and Trust Region Search Directions for Line Search Methods Models for Trust-Region Methods Scaling Exercises 3 Line Search Methods 3.1 Step Length The Wolfe Conditions The Goldstein Conditions Sufficient Decrease and Backtracking 3.2 Convergence of Line Search Methods 3.3 Rate of Convergence Convergence Rate of Steepest Descent Newton's Method Quasi-Newton Methods 3.4 Newton's Method with Hessian Modification Eigenvalue Modification Adding a Multiple of the ldentity Modified Cholesky Factorization Modified Symmetric Indefinite Factorization 3.5 Step-Length Selection Algorithms lnterpolation lnitial Step Length A Line Search A1gorithm for the Wolfe Conditions Notes and References Exercises 4 Trust-Region Methods Outline of the Trust-Region Approach 4.1 A1gorithms Based on the Cauchy Point The Cauchy Point lmpro时ng on the Cauchy Point The Dogleg Method Two-Dinlensional Subspace Mininlization
以下为对购买帮助不大的评价