DECOMP: an Implementation of Dantzig-Wolfe Decomposition for Linear Programming

Rangaraja P. Sundarraj

ISBN 10: 0387971548 / ISBN 13: 9780387971544

Published by Springer New York, Springer New York Nov 1989, 1989

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 216 pp. Englisch.

Seller Inventory # 9780387971544

Bibliographic Details

• Title: DECOMP: an Implementation of Dantzig-Wolfe Decomposition for Linear Programming
• Publisher: Springer New York, Springer New York Nov 1989
• Publication Date: 1989
• Language: English
• ISBN 10: 0387971548
• ISBN 13: 9780387971544
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

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.