Decomposition Techniques in Mathematical Programming: Engineering and Science Applications / Edition 1

by Antonio J. Conejo, Enrique Castillo, Roberto Minguez, Raquel Garcia-Bertrand

Overview

Optimization plainly dominates the design, planning, operation, and c- trol of engineering systems. This is a book on optimization that considers particular cases of optimization problems, those with a decomposable str- ture that can be advantageously exploited. Those decomposable optimization problems are ubiquitous in engineering and science applications. The book considers problems with both complicating constraints and complicating va- ables, and analyzes linear and nonlinear problems, with and without in- ger variables. The decomposition techniques analyzed include Dantzig-Wolfe, Benders, Lagrangian relaxation, Augmented Lagrangian decomposition, and others. Heuristic techniques are also considered. Additionally, a comprehensive sensitivity analysis for characterizing the solution of optimization problems is carried out. This material is particularly novel and of high practical interest. This book is built based on many clarifying, illustrative, and compu- tional examples, which facilitate the learning procedure. For the sake of cl- ity, theoretical concepts and computational algorithms are assembled based on these examples. The results are simplicity, clarity, and easy-learning. We feel that this book is needed by the engineering community that has to tackle complex optimization problems, particularly by practitioners and researchers in Engineering, Operations Research, and Applied Economics. The descriptions of most decomposition techniques are available only in complex and specialized mathematical journals, difficult to understand by engineers. A book describing a wide range of decomposition techniques, emphasizing problem-solving, and appropriately blending theory and application, was not previously available.

Product Details

ISBN-13:	9783642066078
Publisher:	Springer Berlin Heidelberg
Publication date:	11/09/2010
Edition description:	Softcover reprint of hardcover 1st ed. 2006
Pages:	542
Product dimensions:	6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

Motivation and Introduction.- Motivating Examples: Models with Decomposable Structure.- Decomposition Techniques.- Decomposition in Linear Programming: Complicating Constraints.- Decomposition in Linear Programming: Complicating Variables.- Duality.- Decomposition in Nonlinear Programming.- Decomposition in Mixed-Integer Programming.- Other Decomposition Techniques.- Local Sensitivity Analysis.- Local Sensitivity Analysis.- Applications.- Applications.- Computer Codes.- Some GAMS Implementations.- Solution to Selected Exercises.- Exercise Solutions.

Editorial Reviews

From the reviews:

"A review of a large variety of optimization models where decomposition is used, and to present the available methods in a clear, illustrative, and application-oriented way. … The large number of examples and exercises with applications from economics and electrical, mechanical, energy, and civil engineering makes the book extremely valuable for people working in these areas who want to get a quick … and qualified, introduction to relevant decomposition techniques. The large number of exercises makes it attractive as a textbook … ." (K. Schittkowski, Mathematical Reviews, Issue 2007 e)

"Mathematical programming is one of the main techniques used in theoretical and applied operations research (OR). … This book is primarily oriented to the students in science and engineering. However, its material and style of presentation also make it suitable for students of business management, OR, and applied economics. … I think that this book would be valuable in the libraries of all institutions that teach advanced mathematical-programming courses … ." (A. Žilinskas, Interfaces, Vol. 37 (5), 2007)

From the Publisher