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Decomp: An Implementation of Dantzig-Wolfe Decomposition for Linear Programming

AUTHOR Ho, James K.; Sundarraj, Rangaraja P.
PUBLISHER Springer (11/22/1989)
PRODUCT TYPE Paperback (Paperback)

Description
For linear optimization models that can be formulated as linear programs with the block-angular structure, i.e. independent subproblems with coupling constraints, the Dantzig-Wolfe decomposition principle provides an elegant framework of solution algorithms as well as economic interpretation. This monograph is the complete documentation of DECOMP: a robust implementation of the Dantzig-Wolfe decomposition method in FORTRAN. The code can serve as a very convenient starting point for further investigation, both computational and economic, of parallelism in large-scale systems. It can also be used as supplemental material in a second course in linear programming, computational mathematical programming, or large-scale systems.
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Product Details
ISBN-13: 9780387971544
ISBN-10: 0387971548
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
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Page Count: 206
Carton Quantity: 18
Product Dimensions: 8.50 x 0.46 x 11.00 inches
Weight: 1.13 pound(s)
Feature Codes: Illustrated
Country of Origin: DE
Subject Information
BISAC Categories
Mathematics | Linear & Nonlinear Programming
Mathematics | Operations Research
Mathematics | Computer Architecture
Dewey Decimal: 519.72
Library of Congress Control Number: 89021962
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For linear optimization models that can be formulated as linear programs with the block-angular structure, i.e. independent subproblems with coupling constraints, the Dantzig-Wolfe decomposition principle provides an elegant framework of solution algorithms as well as economic interpretation. This monograph is the complete documentation of DECOMP: a robust implementation of the Dantzig-Wolfe decomposition method in FORTRAN. The code can serve as a very convenient starting point for further investigation, both computational and economic, of parallelism in large-scale systems. It can also be used as supplemental material in a second course in linear programming, computational mathematical programming, or large-scale systems.
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Paperback