The original edition of this book was celebrated for its coverage of the central concepts of practical optimization techniques. This updated edition expands and illuminates the connection between the purely analytical character of an optimization problem, expressed by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. Incorporating modern theoretical insights, this classic text is even more useful.
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From the reviews of the second edition:
"I have profitably used the book to apply constrained minimization procedures in the field of computational contact mechanics. I think it is not a secret that quite often books on mathematics are written from mathematicians for mathematicians. Hence it is quite hard for engineers to read and to extract valuable information from them. With this respect this book is a shining star. It presents the topics in a very precise but clear and understandable way."
(Giorgio Azvaris, Turin, Italy)
"I have the 1977 edition from my father's MIT days. I am a Mathematician and I can verify that the book written in 1977 is of the same style that good books have today. A book is not made obsolete because some new "elegant" terms arise."
(A reader from Greece)
"In this second edition ... David Luenberger focuses on practical optimization techniques. ... the book would be appropriate for graduate students or for self-study by professionals. ... I recommend the book for those who are familiar with elements of linear algebra ... . The book concludes with three short appendices ... and a bibliography and a short index. ... is intended for those who want to look deeply into optimization techniques, linear and nonlinear. ... will be useful to researchers, engineers, and graduate students." (Sergio Ubeda, Interfaces, Vol. 37 (1), 2007)
"Linear and Nonlinear Programming" is considered a classic textbook in Optimization. While it is a classic, it also reflects modern theoretical insights. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as a means for learning existing material and for developing new results. One major insight of this type is the connection between the purely analytical character of an optimization problem, expressed perhaps by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. This was a major theme of the first and second editions. Now the third edition has been completely updated with recent Optimization Methods. Yinyu Ye has written chapters and chapter material on a number of these areas including Interior Point Methods.
This book is designed for either self-study by professionals or classroom work at the undergraduate or graduate level for technical students. Like the field of optimization itself, which involves many classical disciplines, the book should be useful to system analysts, operations researchers, numerical analysts, management scientists, and other specialists.
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