Ebook: Decomposition Techniques in Mathematical Programming: Engineering and Science Applications
- Tags: Appl.Mathematics/Computational Methods of Engineering, Operations Research Mathematical Programming, Operations Research/Decision Theory, Applications of Mathematics
- Year: 2006
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
This textbook for students and practitioners presents a practical approach to decomposition techniques in optimization. It provides an appropriate blend of theoretical background and practical applications in engineering and science, which makes the book interesting for practitioners, as well as engineering, operations research and applied economics graduate and postgraduate students. "Decomposition Techniques in Mathematical Programming" is based on clarifying, illustrative and computational examples and applications from electrical, mechanical, energy and civil engineering as well as applied mathematics and economics. It addresses decomposition in linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming, and provides rigorous decomposition algorithms as well as heuristic ones. Practical applications are developed up to working algorithms that can be readily used. The theoretical background of the book is deep enough to be of interest to applied mathematicians. It includes end of chapter exercises and the solutions to the even numbered exercises are included as an appendix.
This textbook for students and practitioners presents a practical approach to decomposition techniques in optimization. It provides an appropriate blend of theoretical background and practical applications in engineering and science, which makes the book interesting for practitioners, as well as engineering, operations research and applied economics graduate and postgraduate students. "Decomposition Techniques in Mathematical Programming" is based on clarifying, illustrative and computational examples and applications from electrical, mechanical, energy and civil engineering as well as applied mathematics and economics. It addresses decomposition in linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming, and provides rigorous decomposition algorithms as well as heuristic ones. Practical applications are developed up to working algorithms that can be readily used. The theoretical background of the book is deep enough to be of interest to applied mathematicians. It includes end of chapter exercises and the solutions to the even numbered exercises are included as an appendix.
This textbook for students and practitioners presents a practical approach to decomposition techniques in optimization. It provides an appropriate blend of theoretical background and practical applications in engineering and science, which makes the book interesting for practitioners, as well as engineering, operations research and applied economics graduate and postgraduate students. "Decomposition Techniques in Mathematical Programming" is based on clarifying, illustrative and computational examples and applications from electrical, mechanical, energy and civil engineering as well as applied mathematics and economics. It addresses decomposition in linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming, and provides rigorous decomposition algorithms as well as heuristic ones. Practical applications are developed up to working algorithms that can be readily used. The theoretical background of the book is deep enough to be of interest to applied mathematicians. It includes end of chapter exercises and the solutions to the even numbered exercises are included as an appendix.
Content:
Front Matter....Pages I-XVI
Front Matter....Pages 1-1
Motivating Examples: Models with Decomposable Structure....Pages 3-64
Front Matter....Pages 65-65
Decomposition in Linear Programming: Complicating Constraints....Pages 67-106
Decomposition in Linear Programming: Complicating Variables....Pages 107-139
Duality....Pages 141-185
Decomposition in Nonlinear Programming....Pages 187-242
Decomposition in Mixed-Integer Programming....Pages 243-270
Other Decomposition Techniques....Pages 271-299
Front Matter....Pages 301-301
Local Sensitivity Analysis....Pages 303-346
Front Matter....Pages 347-347
Applications....Pages 349-393
Front Matter....Pages 395-395
Some GAMS Implementations....Pages 397-417
Front Matter....Pages 419-419
Exercise Solutions....Pages 421-529
Back Matter....Pages 531-541
This textbook for students and practitioners presents a practical approach to decomposition techniques in optimization. It provides an appropriate blend of theoretical background and practical applications in engineering and science, which makes the book interesting for practitioners, as well as engineering, operations research and applied economics graduate and postgraduate students. "Decomposition Techniques in Mathematical Programming" is based on clarifying, illustrative and computational examples and applications from electrical, mechanical, energy and civil engineering as well as applied mathematics and economics. It addresses decomposition in linear programming, mixed-integer linear programming, nonlinear programming, and mixed-integer nonlinear programming, and provides rigorous decomposition algorithms as well as heuristic ones. Practical applications are developed up to working algorithms that can be readily used. The theoretical background of the book is deep enough to be of interest to applied mathematicians. It includes end of chapter exercises and the solutions to the even numbered exercises are included as an appendix.
Content:
Front Matter....Pages I-XVI
Front Matter....Pages 1-1
Motivating Examples: Models with Decomposable Structure....Pages 3-64
Front Matter....Pages 65-65
Decomposition in Linear Programming: Complicating Constraints....Pages 67-106
Decomposition in Linear Programming: Complicating Variables....Pages 107-139
Duality....Pages 141-185
Decomposition in Nonlinear Programming....Pages 187-242
Decomposition in Mixed-Integer Programming....Pages 243-270
Other Decomposition Techniques....Pages 271-299
Front Matter....Pages 301-301
Local Sensitivity Analysis....Pages 303-346
Front Matter....Pages 347-347
Applications....Pages 349-393
Front Matter....Pages 395-395
Some GAMS Implementations....Pages 397-417
Front Matter....Pages 419-419
Exercise Solutions....Pages 421-529
Back Matter....Pages 531-541
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