Overview

Linear Programming (LP) is perhaps the most frequently used optimization technique. One of the reasons for its wide use is that very powerful solution algorithms exist for linear optimization. Computer programs based on either the simplex or interior point methods are capable of solving very large-scale problems with high reliability and within reasonable time. Model builders are aware of this and often try to formulate real-life problems within this framework to ensure they can be solved efficiently. It is also true that many real-life optimization problems can be formulated as truly linear models and also many others can well be approximated by linearization. The two main methods for solving LP problems are the variants of the simplex method and the interior point methods (IPMs). It turns out that both variants have their role in solving different problems. It has been recognized that, since the introduction of the IPMs, the efficiency of simplex-based solvers has increased by two orders of magnitude. This increased efficiency can be attributed to the following: theoretical developments in the underlying algorithms; inclusion of results of computer science; using the principles of software engineering; and taking into account the state-of-the-art in computer technology. This book offers a systematic treatment focused on the computational issues of the simplex method. The purpose is to provide sufficient details about all aspects that are necessary for its successful implementation. On the basis of the book's systematic treatment, high quality implementations will result. Additionally, many of the procedures and techniques presented here can also be used in the efficient implementation of other optimization algorithms.

Full Product Details

Author:   István Maros
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2003 ed.
Volume:   61
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   1.480kg
ISBN:  

9781402073328

ISBN 10:   1402073321
Pages:   325
Publication Date:   31 December 2002
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

I Preliminaries.- 1. The Linear Programming Problem.- 2. The Simplex Method.- 3. Large Scale LP Problems.- II Computational Techniques.- 4. Design Principles of LP Systems.- 5. Data Structures and Basic Operations.- 6. Problem Definition.- 7. LP Preprocessing.- 8. Basis Inverse, Factorization.- 9. The Primal Algorithm.- 10. The Dual Algorithm.- 11. Various Issues.

Reviews

This is really a nice, long awaited book...it covers all important aspects and techniques needed for an efficient, robust implementation of the simplex method...it deserves a place on the bookshelf of every OR, optimization professional, it could be marketed as handbook of computational techniques. <br>(TamAs Terlaky, Dept. of Computing and Software, McMaster University, Hamilton, ON, Canada)<br> The book will be of great interest to people developing advanced LP solver codes customized for special purposes, and solvers for integer programming and combinatorial optimization, and also for researchers working in these areas. It is an ideal textbook for graduate courses in computational mathematical programming. It deserves to be in the personal library of software engineers dealing with numerical computation involving linear constraints. <br>(K.G. Murty, for the American Mathematical Society, MathSciNet Mathematical Reviews on the web)

This is really a nice, long awaited book...it covers all important aspects and techniques needed for an efficient, robust implementation of the simplex method...it deserves a place on the bookshelf of every OR, optimization professional, it could be marketed as handbook of computational techniques . (Tamas Terlaky, Dept. of Computing and Software, McMaster University, Hamilton, ON, Canada) The book will be of great interest to people developing advanced LP solver codes customized for special purposes, and solvers for integer programming and combinatorial optimization, and also for researchers working in these areas. It is an ideal textbook for graduate courses in computational mathematical programming. It deserves to be in the personal library of software engineers dealing with numerical computation involving linear constraints. (K.G. Murty, for the American Mathematical Society, MathSciNet Mathematical Reviews on the web)

This is really a nice, long awaited book...it covers all important aspects and techniques needed for an efficient, robust implementation of the simplex method...it deserves a place on the bookshelf of every OR, optimization professional, it could be marketed as handbook of computational techniques . (Tamas Terlaky, Dept. of Computing and Software, McMaster University, Hamilton, ON, Canada) The book will be of great interest to people developing advanced LP solver codes customized for special purposes, and solvers for integer programming and combinatorial optimization, and also for researchers working in these areas. It is an ideal textbook for graduate courses in computational mathematical programming. It deserves to be in the personal library of software engineers dealing with numerical computation involving linear constraints. (K.G. Murty, for the American Mathematical Society, MathSciNet Mathematical Reviews on the web)

Author Information

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions