This book is intended as a text covering the central concepts of practical optimization
techniques. It is designed for either self-study by professionals or classroom work at
the undergraduate or graduate level for students who have a technical background
in engineering, mathematics, or science. 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 from the host of disciplines from which practical optimization applications
are drawn. The prerequisites for convenient use of the book are relatively
modest; the prime requirement being some familiarity with introductory elements
of linear algebra. Certain sections and developments do assume some knowledge
of more advanced concepts of linear algebra, such as eigenvector analysis, or some
background in sets of real numbers, but the text is structured so that the mainstream
of the development can be faithfully pursued without reliance on this more advanced
background material.
Although the book covers primarily material that is now fairly standard, it
is intended to reflect modern theoretical insights. These 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 edition of this book and the second edition expands and further
illustrates this relationship.