As the Solutions Manual, this book is meant to accompany the main
title, Nonlinear Programming: Theory and Algorithms, Third
Edition. This book presents recent developments of key
topics in nonlinear programming (NLP) using a logical and
self-contained format. The volume is divided into three sections:
convex analysis, optimality conditions, and dual computational
techniques. Precise statements of algortihms are given along with
convergence analysis. Each chapter contains detailed numerical
examples, graphical illustrations, and numerous exercises to aid
readers in understanding the concepts and methods discussed.
Autorentext
Mokhtar S. Bazaraa and C.M. Shetty are Professors Emeriti at Georgia Institute of Technology. Hanif D. Sherali, the lead author, is a W. Thomas Rice Chaired Professor of Engineering in the Grado Department of Industrial and Systems Engineering at the Virginia Polytechnic and State University. He and Dr. Bazaraa are co-authors of a complementary best-selling book at Wiley on linear programming (LP). Solutions prepared by Joanna Leleno.
Zusammenfassung
As the Solutions Manual, this book is meant to accompany the main title, Nonlinear Programming: Theory and Algorithms, Third Edition. This book presents recent developments of key topics in nonlinear programming (NLP) using a logical and self-contained format. The volume is divided into three sections: convex analysis, optimality conditions, and dual computational techniques. Precise statements of algortihms are given along with convergence analysis. Each chapter contains detailed numerical examples, graphical illustrations, and numerous exercises to aid readers in understanding the concepts and methods discussed.
Inhalt
Chapter 1: Introduction 1
1.1, 1.2, 1.4, 1.6, 1.10, 1.13
Chapter 2 Convex Sets 4
2.1, 2.2, 2.3, 2.7, 2.8, 2.12, 2.15, 2.21, 2.24, 2.31, 2.42, 2.45, 2.47, 2.49, 2.50, 2.51, 2.52, 2.53, 2.57
Chapter 3: Convex Functions and Generalizations 15
3.1, 3.2, 3.3, 3.4, 3.9, 3,10, 3.11, 3.16, 3.18, 3.21, 3.22, 3.26, 3.27, 3.28, 3.31, 3.37, 3.39, 3.40, 3.41, 3.45, 3.48, 3.51, 3.54, 3.56, 3.61, 3.62, 3.63, 3.64, 3.65
Chapter 4: The Fritz John and Karush-Kuhn-Tucker Optimality Conditions 29
4.1, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 4.10, 4.12, 4.15, 4.27, 4.28, 4.30, 4.31, 4.33, 4.37, 4.41, 4.43
Chapter 5: Constraint Qualifications 46
5.1, 5.12, 5.13, 5.15, 5.20
Chapter 6: Lagrangian Duality and Saddle Point Optimality Conditions 51
6.2, 6.3, 6.4, 6.5, 6.7, 6.8, 6.9, 6.14, 6.15, 6.21, 6.23, 6.27, 6.29,
Chapter 7: The Concept of an Algorithm 64
7.1, 7.2, 7.3, 7.6, 7.7, 7.19
Chapter 8: Unconstrained Optimization 69
8.10, 8.11, 8.12, 8.18, 8.19, 8.21, 8.23, 8.27, 8.28, 8.32, 8.35, 8.41, 8.47, 8.51, 8.52
Chapter 9: Penalty and Barrier Functions 88
9.2, 9.7, 9.8, 9.12, 9.13, 9.14, 9.16, 9.19, 9.32
Chapter 10: Methods of Feasible Directions 107
10.3, 10.4, 10.9, 1.012, 10.19, 10.20, 10.25, 10.33, 10.36, 10.41, 10.44, 10.47, 10.52
Chapter 11: Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programing 134
11.1, 11.5, 11.12, 11.18, 11.19, 11.22, 11.23, 11.24, 11.36, 11.41, 11.42, 11.47, 11.48, 11.50, 11.51, 11.52