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.
