東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linear programming = foundations and...

Vanderbei, Robert J.

Linked to FindBook

Google Book

Amazon

博客來

Linear programming = foundations and extensions /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Linear programming/ by Robert J. Vanderbei.
Reminder of title:	foundations and extensions /
Author:	Vanderbei, Robert J.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xxv, 471 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1. Introduction -- Chapter 2. The Simplex Method -- Chapter 3. Degeneracy -- Chapter 4. Efficiency of the Simplex Method -- Chapter 5. Duality Theory -- Chapter 6. The Simplex Method in Matrix Notational -- Chapter 7. Sensitivity and Parametric Analyses -- Chapter 8. Implementation Issues -- Chapter 9. Problems in General Form -- Chapter 10. Convex Analysis -- Chapter 11. Game Theory -- Chapter 12. Data Science Applications -- Chapter 13. Financial Applications -- Chapter 14. Network Flow Problems -- Chapter 15. Applications -- Chapter 16. Structural Optimization -- Chapter 17. The Central Path -- Chapter 18. A Path-Following Method -- Chapter 19. The KKT System -- Chapter 20. Implementation Issues -- Chapter 21. The Affine-Scaling Method -- Chapter 22. The Homogeneous Self-Dual Method -- Chapter 23. Integer Programming -- Chapter 24. Quadratic Programming -- Chapter 25. Convex Programming.
Contained By:	Springer eBooks
Subject:	Linear programming. -
Online resource:	https://doi.org/10.1007/978-3-030-39415-8
ISBN:	9783030394158

Linear programming = foundations and extensions /
Vanderbei, Robert J.

Linear programmingfoundations and extensions /[electronic resource] :by Robert J. Vanderbei. - Fifth edition. - Cham :Springer International Publishing :2020. - xxv, 471 p. :ill. (some col.), digital ;24 cm. - International series in operations research & management science,v.2850884-8289 ;. - International series in operations research & management science ;v.285..

Chapter 1. Introduction -- Chapter 2. The Simplex Method -- Chapter 3. Degeneracy -- Chapter 4. Efficiency of the Simplex Method -- Chapter 5. Duality Theory -- Chapter 6. The Simplex Method in Matrix Notational -- Chapter 7. Sensitivity and Parametric Analyses -- Chapter 8. Implementation Issues -- Chapter 9. Problems in General Form -- Chapter 10. Convex Analysis -- Chapter 11. Game Theory -- Chapter 12. Data Science Applications -- Chapter 13. Financial Applications -- Chapter 14. Network Flow Problems -- Chapter 15. Applications -- Chapter 16. Structural Optimization -- Chapter 17. The Central Path -- Chapter 18. A Path-Following Method -- Chapter 19. The KKT System -- Chapter 20. Implementation Issues -- Chapter 21. The Affine-Scaling Method -- Chapter 22. The Homogeneous Self-Dual Method -- Chapter 23. Integer Programming -- Chapter 24. Quadratic Programming -- Chapter 25. Convex Programming.

The book provides a broad introduction to both the theory and the application of optimization with a special emphasis on the elegance, importance, and usefulness of the parametric self-dual simplex method. The book assumes that a problem in "standard form," is a problem with inequality constraints and nonnegative variables. The main new innovation to the book is the use of clickable links to the (newly updated) online app to help students do the trivial but tedious arithmetic when solving optimization problems. The latest edition now includes: a discussion of modern Machine Learning applications, as motivational material; a section explaining Gomory Cuts and an application of integer programming to solve Sudoku problems. 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, the primal-dual simplex method, the path-following interior-point method, and and the homogeneous self-dual method. In addition, the author provides online tools that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and online pivot tools can be found on the book's website. The website also includes new online instructional tools and exercises.

ISBN: 9783030394158

Standard No.: 10.1007/978-3-030-39415-8doiSubjects--Topical Terms:

560448
Linear programming.

LC Class. No.: T57.74 / .V363 2020

Dewey Class. No.: 519.6

Linear programming = foundations and extensions /
LDR:03629nmm a2200361 a 4500 001 2217534
003 DE-He213
005 20200731145400.0
006 m d
007 cr nn 008maaau
008 201120s2020 sz s 0 eng d
020 $a 9783030394158 $q (electronic bk.)
020 $a 9783030394141 $q (paper)
024 7 $a 10.1007/978-3-030-39415-8 $2 doi
035 $a 978-3-030-39415-8
040 $a GP $c GP
041 0 $a eng
050 4 $a T57.74 $b .V363 2020
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 519.6 $2 23
090 $a T57.74 $b .V228 2020
100 1 $a Vanderbei, Robert J. $3 757109
245 1 0 $a Linear programming $h [electronic resource] : $b foundations and extensions / $c by Robert J. Vanderbei.
250 $a Fifth edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xxv, 471 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a International series in operations research & management science, $x 0884-8289 ; $v v.285
505 0 $a Chapter 1. Introduction -- Chapter 2. The Simplex Method -- Chapter 3. Degeneracy -- Chapter 4. Efficiency of the Simplex Method -- Chapter 5. Duality Theory -- Chapter 6. The Simplex Method in Matrix Notational -- Chapter 7. Sensitivity and Parametric Analyses -- Chapter 8. Implementation Issues -- Chapter 9. Problems in General Form -- Chapter 10. Convex Analysis -- Chapter 11. Game Theory -- Chapter 12. Data Science Applications -- Chapter 13. Financial Applications -- Chapter 14. Network Flow Problems -- Chapter 15. Applications -- Chapter 16. Structural Optimization -- Chapter 17. The Central Path -- Chapter 18. A Path-Following Method -- Chapter 19. The KKT System -- Chapter 20. Implementation Issues -- Chapter 21. The Affine-Scaling Method -- Chapter 22. The Homogeneous Self-Dual Method -- Chapter 23. Integer Programming -- Chapter 24. Quadratic Programming -- Chapter 25. Convex Programming.
520 $a The book provides a broad introduction to both the theory and the application of optimization with a special emphasis on the elegance, importance, and usefulness of the parametric self-dual simplex method. The book assumes that a problem in "standard form," is a problem with inequality constraints and nonnegative variables. The main new innovation to the book is the use of clickable links to the (newly updated) online app to help students do the trivial but tedious arithmetic when solving optimization problems. The latest edition now includes: a discussion of modern Machine Learning applications, as motivational material; a section explaining Gomory Cuts and an application of integer programming to solve Sudoku problems. 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, the primal-dual simplex method, the path-following interior-point method, and and the homogeneous self-dual method. In addition, the author provides online tools that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and online pivot tools can be found on the book's website. The website also includes new online instructional tools and exercises.
650 0 $a Linear programming. $3 560448
650 0 $a Mathematical optimization. $3 517763
650 1 4 $a Operations Research/Decision Theory. $3 890895
650 2 4 $a Optimization. $3 891104
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 891214
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a International series in operations research & management science ; $v v.285. $3 3450822
856 4 0 $u https://doi.org/10.1007/978-3-030-39415-8
950 $a Business and Management (Springer-41169)