"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. The new co-author, Yinyu Ye, has written chapters and chapter material on a number of these areas including Interior Point Methods.

The 1st edition of this book is considered a classic; the 2nd edition expanded on the theme, and the 3rd edition will update the material with the help of a new co-author, Yinyu Ye Provides a structure for learning existing material, and insight for developing new results Useful to analysts, operations researchers and management experts in many fields

Autorentext
David G. Luenberger has directed much of his career toward teaching "portable concepts" - organizing theory around concepts and actually "porting" the concepts to applications where, in the process, the general concepts are often discovered. The search for fundamentals has explicitly directed his research in the fields of control, optimization, planning, economics, and investments, and in turn, it is the discovery of these fundamentals that have motivated his textbook writing projects.

Inhalt
Linear Programming.- Basic Properties of Linear Programs.- The Simplex Method.- Duality.- Interior-Point Methods.- Transportation and Network Flow Problems.- Unconstrained Problems.- Basic Properties of Solutions and Algorithms.- Basic Descent Methods.- Conjugate Direction Methods.- Quasi-Newton Methods.- Constrained Minimization.- Constrained Minimization Conditions.- Primal Methods.- Penalty and Barrier Methods.- Dual and Cutting Plane Methods.- Primal-Dual Methods.