This textbook provides a selfcontained introduction to linear programming using MATLAB(R) software to elucidate the development of algorithms and theory. Early chapters cover linear algebra basics, the simplex method, duality, the solving of large linear problems, sensitivity analysis, and parametric linear programming. In later chapters, the authors discuss quadratic programming, linear complementarity, interiorpoint methods, and selected applications of linear programming to approximation and classification problems. Exercises are interwoven with the theory presented in each chapter, and two appendices provide additional information on linear algebra, convexity, nonlinear functions, and on available MATLAB commands, respectively. Readers can access MATLAB codes and associated mex files at a Web site maintained by the authors. Only a basic knowledge of linear algebra and calculus is required to understand this textbook, which is geared toward junior and seniorlevel undergraduate students, firstyear graduate students, and researchers unfamiliar with linear programming.
About Michael C. Ferris
Michael C. Ferris is a Professor in the Computer Sciences Department at the University of WisconsinMadison. Olvi L. Mangasarian is John von Neumann Professor Emeritus of Mathematics and Computer Sciences at the University of WisconsinMadison. Stephen J. Wright is a Professor in the Computer Sciences Department at the University of WisconsinMadison.Details Book
Author  :  Michael C. Ferris 
Publisher  :  Society for Industrial 
Data Published  :  31 January 2008 
ISBN  :  0898716438 
EAN  :  9780898716436 
Format Book  :  PDF, Epub, DOCx, TXT 
Number of Pages  :  280 pages 
Age +  :  15 years 
Language  :  English 
Rating  : 
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