Linear Programming Using MATLAB®

Author:   Nikolaos Ploskas ,  Nikolaos Samaras
Publisher:   Springer International Publishing AG
Edition:   Softcover reprint of the original 1st ed. 2017
ISBN:  

9783319881317


Pages:   637
Publication Date:   25 August 2018
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Linear Programming Using MATLAB®


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Overview

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.

Full Product Details

Author:   Nikolaos Ploskas ,  Nikolaos Samaras
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   Softcover reprint of the original 1st ed. 2017
Weight:   0.997kg
ISBN:  

9783319881317


ISBN 10:   3319881310
Pages:   637
Publication Date:   25 August 2018
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Introduction.- 2. Linear Programming Algorithms.- 3. Linear Programming Benchmark and Random Problems.- 4. Presolve Methods.- 5. Scaling Techniques.- 6. Pivoting Rules.- 7. Basis Inverse and  Update Methods.- 8. Revised Primal Simplex Algorithm.- 9. Exterior Point Simplex Algorithms.- 10. Interior Point Method.- 11. Sensitivity Analysis.- Appendix: MATLAB’s Optimization Toolbox Algorithms.-  Appendix: State-of-the-art Linear Programming Solvers;CLP and CPLEX.

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