Ross Baldick

Applied Optimization (eBook, ePUB)

Formulation and Algorithms for Engineering Systems

• Format: ePub

Produktbeschreibung

The starting point in the formulation of any numerical problem is to take an intuitive idea about the problem in question and to translate it into precise mathematical language. This book provides step-by-step descriptions of how to formulate numerical problems and develops techniques for solving them. A number of engineering case studies motivate the development of efficient algorithms that involve, in some cases, transformation of the problem from its initial formulation into a more tractable form. Five general problem classes are considered: linear systems of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization. The book contains many worked examples and homework exercises and is suitable for students of engineering or operations research taking courses in optimization. Supplementary material including solutions, lecture slides and appendices are available online at www.cambridge.org/9780521855648.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 18. Januar 2009
• Englisch
• ISBN-13: 9781107386181
• Artikelnr.: 40022527

Autorenporträt

ROSS BALDICK is a professor of electrical and computer engineering at the University of Texas at Austin. His current research involves optimization and economic theory applied to electric power system operations and the public policy and technical issues associated with electric transmission under deregulation. He is an associate editor of IEEE Transactions on Power Systems and the chairman of the System Economics Sub-Committee of the IEEE Power Engineering

Inhaltsangabe

List of illustrations
Preface
1. Introduction
2. Problems, algorithms and solutions
3. Transformation of problems
Part I: Linear simultaneous equations
4. Case studies
5. Algorithms
Part II: Non-linear simultaneous equations
6. Case Studies
7. Algorithms
8. Solution of the case studies
Part III: Unconstrained optimization
9. Case studies
10 Algorithms
11. Solution of the case studies
Part IV: Equality-constrained optimization
12. Case studies
13. Algorithms for linear constraints
14. Algorithms for non-linear constraints
Part V: Inequality-constrained optimization
15. Case studies
16. Algorithms for non-negativity constraints
17. Algorithms for linear constraints
18. Solution of the linearly constrained case studies
19. Algorithms for non-linear constraints
20. Solution of the non-linearly constrained case studies
References
Index
Appendices.