Synopses & Reviews
This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book, on the other hand, is the first text to use Mathematica to develop a thorough understanding of optimization algorithms, fully exploiting Mathematica's symbolic, numerical and graphic capabilities.
This practical and intuitive introduction to optimization theory and computational algorithms features a cross-platform CD-ROM containing all the text, examples, "Mathematica 3.0" functions, and Notebooks. This is the first textbook to use "Mathematica" to develop a thorough understanding of optimization algorithms, fully exploiting "Mathematica's" symbolic, numerical, and graphical capabilities. 176 illus.
The goal of this book is to present basic optimization theory and modern computational algorithms in a concise manner. The book is suitable for un dergraduate and graduate students in all branches of engineering, operations research, and management information systems. The book should also be use ful for practitioners who are interested in learning optimization and using these techniques on their own. Most available books in the field tend to be either too theoretical or present computational algorithms in a cookbook style. An approach that falls some where in between these two extremes is adopted in this book. Theory is pre sented in an informal style to make sense to most undergraduate and graduate students in engineering and business. Computational algorithms are also de veloped in an informal style by appealing to readers' intuition rather than mathematical rigor. The available, computationally oriented books generally present algorithms alone and expect readers to perform computations by hand or implement these algorithms by themselves. This obviously is unrealistic for a usual introductory optimization course in which a wide variety of optimization algorithms are discussed. There are some books that present programs written in traditional computer languages such as Basic, FORTRAN, or Pascal. These programs help with computations, but are of limited value in developing understanding of the algorithms because very little information about the intermediate steps v ' Preface VI -------------------------------------------------------- is presented."
Includes bibliographical references (p. 705-708) and index.
Table of Contents
Optimization Problem Formulation.- Graphical Optimization.- Mathematical Preliminaries.- Optimality Conditions.- Unconstrained Problems.- Linear Programming.- Interior Point Methods.- Quadratic Programming.- Nonlinear Constrained Problems.- Appendix.- Introduction to Mathematica.