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Linear Programming Using MATLAB®

Nikolaos Samaras, Nikolaos Ploskas

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Sonstiges

Beschreibung

This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book  are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms.

As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus.  The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.

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Schlagwörter

scaling techniques, Convert MPS2MAT, parametric programming, Interior Point Methods, sensitivity analysis, Sensitivity Analysis, matlab Optimization toolbox, MATLAB linear programming, Presolve Methods, Linear Programming Problem, linear programming algorithms, simplex algorithm, Geometry of Linear Programming Problems, Convert MAT2MPS, Pivoting Rules, matlab toolbox, Gauss-Jordan Elimination, Revised Primal Simplex Algorithm, Revised Dual Simplex Algorithm, Exterior Point Simplex Algorithm