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Linear Programming
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Table of Contents

Introduction.- The Simplex Method.- Degeneracy.- Efficiency of the Simplex Method.- Duality Theory.- The Simplex Method in Matrix Notation.- Sensitivity and Parametric Analyses.- Implementation Issues.- Problems in General Form.- Convex Analysis.- Game Theory.- Regression.- Financial Applications.- Network-Type Problems.- Applications.- Structural Optimization.- The Central Path.- A Path-Following Method.- The KKT System.- Implementation Issues.- The Affine-Scaling Method.- The Homogeneous Self-Dual Method.- Integer Programming.- Quadratic Programming.- Convex Programming.

About the Author

Robert J. Vanderbei is Professor of Operations Research and Financial Engineering, and Department Chair, OR and Financial Engineering at Princeton University. His research interests are in algorithms for nonlinear optimization and their application to problems arising in engineering and science. Application areas of interest focus mainly on inverse Fourier transform optimization problems and action minimization problems with a special interest in applying these techniques to the design of NASA's terrestrial planet finder space telescope.

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