Linear Programming: Foundations and Extensions
Autor Robert J Vanderbeien Limba Engleză Hardback – 31 dec 1996
This book aims to be the first introduction to the topic. Specific examples and concrete algorithms precede more abstract topics. Nevertheless, topics covered are developed in some depth, a large number of numerical examples worked out in detail, and many recent results are included, most notably interior-point methods. The exercises at the end of each chapter both illustrate the theory, and, in some cases, extend it.
Optimization is not merely an intellectual exercise: its purpose is to solve practical problems on a computer. Accordingly, the book comes with software that implements the major algorithms studied. At this point, software for the following four algorithms is available:
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (1) | 470.43 lei 38-44 zile | |
| Springer Us – 8 aug 2015 | 470.43 lei 38-44 zile | |
| Hardback (1) | 1180.15 lei 43-57 zile | |
| Springer Us – 31 dec 1996 | 1180.15 lei 43-57 zile |
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Specificații
ISBN-13: 9780792398042
ISBN-10: 0792398041
Pagini: 418
Ilustrații: XVIII, 418 p.
Dimensiuni: 160 x 241 x 29 mm
Greutate: 0.82 kg
Ediția:1997 edition
Editura: Springer Us
Locul publicării:New York, NY, United States
ISBN-10: 0792398041
Pagini: 418
Ilustrații: XVIII, 418 p.
Dimensiuni: 160 x 241 x 29 mm
Greutate: 0.82 kg
Ediția:1997 edition
Editura: Springer Us
Locul publicării:New York, NY, United States
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Public țintă
ResearchRecenzii
`Vanderbei's book is thoroughly modern. Vanderbei's book has many novel features. Some nice features. This book has style. Overall, I greatly enjoyed reviewing this book, and I highly recommend it as a textbook for an advanced undergraduate or master's level course in linear programming, particularly for courses in an engineering environment. In addition, it also is a good reference book for interior point methods as well as for implementation and computational aspects of linear programming. This is an excellent new book.'
Robert Freund, (MIT) in Optima, 56 (1997)
`In conclusion, Vanderbei's book gives an excellent introduction to linear programminbg, especially the algorithmic side of the subject. The book is highly recommended for both self study and as teaching material.'
Optima, 58 (1998)
Robert Freund, (MIT) in Optima, 56 (1997)
`In conclusion, Vanderbei's book gives an excellent introduction to linear programminbg, especially the algorithmic side of the subject. The book is highly recommended for both self study and as teaching material.'
Optima, 58 (1998)
Descriere
Descriere de la o altă ediție sau format:
This Fourth Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with a substantial treatment of linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Readers will discover a host of practical business applications as well as non-business applications.
Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, primal-dual simplex method, path-following interior-point method, and homogeneous self-dual methods. In addition, the author provides online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's website. The website also includes new online instructional tools and exercises.
This Fourth Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with a substantial treatment of linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Readers will discover a host of practical business applications as well as non-business applications.
Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, primal-dual simplex method, path-following interior-point method, and homogeneous self-dual methods. In addition, the author provides online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's website. The website also includes new online instructional tools and exercises.
Cuprins
Introduction.-
The
Simplex
Method.-
Degeneracy.-
Efficiency
of
the
Simplex
Method.-
Duality
Theory.-
The
Simplex
Method
in
Matrix
Notation.-
Sensitivity
and
Parametric
Analyses.-
Implementation
Issues.-
Problems
in
General
Form.-
Convex
Analysis.-
Game
Theory.-
Regression.-
Financial
Applications.-
Network-Type
Problems.-
Applications.-
Structural
Optimization.-
The
Central
Path.-
A
Path-Following
Method.-
The
KKT
System.-
Implementation
Issues.-
The
Affine-Scaling
Method.-
The
Homogeneous
Self-Dual
Method.-
Integer
Programming.-
Quadratic
Programming.-
Convex
Programming.
Notă biografică
Robert
J.
Vanderbei
is
Professor
of
Operations
Research
and
Financial
Engineering,
and
Department
Chair,
OR
and
Financial
Engineering
at
Princeton
University.
His
research
interests
are
in
algorithms
for
nonlinear
optimization
and
their
application
to
problems
arising
in
engineering
and
science.
Application
areas
of
interest
focus
mainly
on
inverse
Fourier
transform
optimization
problems
and
action
minimization
problems
with
a
special
interest
in
applying
these
techniques
to
the
design
of
NASA’s
terrestrial
planet
finder
space
telescope.
Textul de pe ultima copertă
This
Fourth
Edition
introduces
the
latest
theory
and
applications
in
optimization.
It
emphasizes
constrained
optimization,
beginning
with
a
substantial
treatment
of
linear
programming
and
then
proceeding
to
convex
analysis,
network
flows,
integer
programming,
quadratic
programming,
and
convex
optimization.
Readers
will
discover
a
host
of
practical
business
applications
as
well
as
non-business
applications.
Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, primal-dual simplex method, path-following interior-point method, and homogeneous self-dual methods. In addition, the author provides online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's website. The website also includes new online instructional tools and exercises.
Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, primal-dual simplex method, path-following interior-point method, and homogeneous self-dual methods. In addition, the author provides online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's website. The website also includes new online instructional tools and exercises.
Caracteristici
Complete
updating
of
bestselling
text
in
the
field
Includes online chapter problems at author website
Significant new material about the average-case behavior of the various algorithms covered
Includes online chapter problems at author website
Significant new material about the average-case behavior of the various algorithms covered