Title Details

EDWIN K. P. CHONG, PhD, is Professor of Electrical and Computer Engineering at Colorado State University, Fort Collins, Colorado. He was an Associate Editor for the IEEE Transactions on Automatic Control and received the 1998 ASEE Frederick Emmons Terman Award.
STANISLAW H. ZAK, PhD, is Professor in the School of Electrical and Computer Engineering at Purdue University, West Lafayette, Indiana. He was an Associate Editor of Dynamics and Control and the IEEE Transactions on Neural Networks.

Preface. xiii

PART I MATHEMATICAL REVIEW

Methods of Proof and Some Notation 1

Vector Spaces and Matrices 5

Transformations 21

Concepts from Geometry 39

Elements of Calculus 49

Part II UNCONSTRAINED OPTIMIZATION

Basics of Set-Constrained and Unconstrained Optimization 73

One-Dimensional Search Methods 91

Gradient Methods 113

Newton's Method 139

Conjugate Direction Methods 151

Quasi-Newton Methods 167

Solving Ax = b 187

Unconstrained Optimization and Neural Networks 219

Genetic Algorithms 237

Part III LINEAR PROGRAMMING

Introduction to Linear Programming. 255

Simplex Method 287

Duality 321

Non-Simplex Methods 339

Part IV NONLINEAR CONSTRAINED OPTIMIZATION

Problems with Equality Constraints 365

Problems with Inequality Constraints 397

Convex Optimization Problems 417

Algorithms for Constrained Optimization 439

References 455

Index 462

"...an excellent introduction to optimization theory..." (Journal of Mathematical Psychology, 2002)

"A textbook for a one-semester course on optimization theory and methods at the senior undergraduate or beginning graduate level." (SciTech Book News, Vol. 26, No. 2, June 2002)