Linear Network Optimization: Algorithms and Codes

Read * Linear Network Optimization: Algorithms and Codes PDF by ^ Dimitri P. Bertsekas eBook or Kindle ePUB Online free. Linear Network Optimization: Algorithms and Codes Bertsekas focuses on the algorithms that have proved successful in practice and provides FORTRAN codes that implement them. Its coverage of both theory and implementations make it particularly useful as a text for a graduate-level course on network optimization as well as a practical guide to state-of-the-art codes in the field. Many illustrations, examples, and exercises are included in the text.Contents: Introduction. Dual Ascent Methods. Auction Algorithms. Large-scale optimization is

Linear Network Optimization: Algorithms and Codes

Author :
Rating : 4.98 (543 Votes)
Asin : 0262023342
Format Type : paperback
Number of Pages : 373 Pages
Publish Date : 2015-08-07
Language : English

DESCRIPTION:

Dimitri P. Bertsekas is Professor of Electrical Engineering and Computer Science at MIT.

Bertsekas focuses on the algorithms that have proved successful in practice and provides FORTRAN codes that implement them. Its coverage of both theory and implementations make it particularly useful as a text for a graduate-level course on network optimization as well as a practical guide to state-of-the-art codes in the field. Many illustrations, examples, and exercises are included in the text.Contents: Introduction. Dual Ascent Methods. Auction Algorithms. Large-scale optimization is becoming increasingly important for students and professionals in electrical and industrial engineering, computer science, management science and operations research, and applied mathematics.Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems. It is the first text to clearly explain important recent algorithms such as auction and relaxation, proposed by the author and others for the solution of these problems. Simplex Methods. The presentation is clear, mathematically rigorous, and economical. Appendixes.. Performance and Comparisons

"Very clear exposition" according to Vinz. Very few mistakes, understandable proofs and examples. You'd probably need a math minor or basic undergrad engineering background to understand the entire book - nothing more is assumed. If you want to learn about network optimization, then this book is a great start. It's also a good introduction to standard optimization algorithms, such as duality and simplex methods for linear programming.

Bertsekas is Professor of Electrical Engineering and Computer Science at MIT. . About the Author Dimitri P

OTHER BOOK COLLECTION