Research Catalog

Interior point methods for linear optimization

Title
Interior point methods for linear optimization / by Cornelis Roos, Tamás Terlaky, Jean-Philippe Vial.
Author
Roos, Cornelis, 1941-
Publication
New York : Springer, [2006], ©2006.

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TextRequest in advance T57.74 .R664 2006Off-site

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Details

Additional Authors
  • Terlaky, Tamás.
  • Vial, J. P.
Description
xxiv, 497 pages : illustrations; 24 cm
Summary
"This book is intended for the optimization researcher community, as well as advanced undergraduate and graduate students who are interested in learning the fundamentals and major variants of Interior Point Methods for linear optimization, and who want to have a comprehensive Introduction to Interior Point Methods that revolutionized the theory and practice of modern optimization."--BOOK JACKET.
Subjects
Note
  • Rev. ed. of: Theory and algorithms for linear optimization. c1997.
Bibliography (note)
  • Includes bibliographical references and indexes.
Contents
1. Introduction -- 2. Duality theory for linear optimization -- 3. A polynomial algorithm for the self-dual model -- 4. Solving the canonical problem -- 5. Preliminaries -- 6. The dual logarithmic barrier method -- 7. The primal-dual logarithmic barrier method -- 8. Initialization -- 9. Preliminaries -- 10. The primal-dual Newton method -- 11. Applications -- 12. The dual Newton method -- 13. The primal Newton method -- 14. Application to the method of centers -- 15. Karmarkar's projective method -- 16. More properties of the central path -- 17. Partial updating -- 18. Higher-order methods -- 19. Parametric and sensitivity analysis -- 20. Implementing interior point methods -- App. A. Some results from analysis -- App. B. Pseudo-inverse of a matrix -- App. C. Some technical lemmas -- App. D. Transformation to canonical form -- App. E. The Dikin step algorithm.
ISBN
  • 0387263780 (alk. paper)
  • 0387263799 (e-book)
LCCN
  • 2005049785
  • 9780387263786
  • 9780387263793
OCLC
  • ocm60500551
  • SCSB-5220089
Owning Institutions
Columbia University Libraries