Title Statements
- Full title :Linear programming using MATLAB / Nikolaos Ploskas, Nikolaos Samaras.
Summary
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.
Read More ↓Edition Statements
- Publication Date:2017
Publication Statements
- Publisher(s):Springer
- Place of Publication:Cham, Switzerland
- Language:eng
- Publication Date:2017
The Physical Object
- Description:xvii, 637 pages : : illustrations (black and white) ; : 25 cm.
Edition Identifiers
- ISBN:9783319659176, 3319659170
- oclc:on1064632637
- LC Classification:QA402.5-402.6
- Dewey Decimal:519.6
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.
Read More ↓
Rate & Review