Computational Techniques of the Simplex Method is a systematic treatment focused on the computational issues of the simplex method. It provides a comprehensive coverage of the most important and successful algorithmic and implementation techniques of the simplex method. It is a unique source of essential, never discussed details of algorithmic elements and their implementation. On the basis of the book the reader will be able to create a highly advanced implementation of the simplex method which, in turn, can be used directly or as a building block in other solution algorithms.
Rezensionen / Stimmen
"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"."
(Tamás 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)
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Research
Illustrationen
Maße
Höhe: 241 mm
Breite: 160 mm
Dicke: 24 mm
Gewicht
ISBN-13
978-1-4020-7332-8 (9781402073328)
DOI
10.1007/978-1-4615-0257-9
Schweitzer Klassifikation
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.
