Applied Optimization Formulation and Algorithms for Engineering Systems

ISBN-10: 0521100283

ISBN-13: 9780521100281

Edition: 2009

Authors: Ross Baldick
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Description: 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 so that they can be solved by existing software. It examines various types of numerical problems and develops techniques for solving them. A number of engineering case studies are used to illustrate in detail the formulation process. The 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.

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Book details

Copyright year: 2009
Publisher: Cambridge University Press
Publication date: 1/18/2009
Binding: Paperback
Pages: 792
Size: 6.75" wide x 9.75" long x 1.00" tall
Weight: 2.794
Language: English

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

List of illustrations
Preface
Introduction
Problems, algorithms and solutions
Transformation of problems
Linear simultaneous equations
Case studies
Algorithms
Non-linear simultaneous equations
Case Studies
Algorithms
Solution of the case studies
rUnconstrained optimization
Case studies
Algorithms
Solution of the case studies
Equality-constrained optimization
Case studies
Algorithms for linear constraints
Algorithms for non-linear constraints
Inequality-constrained optimization
Case studies
Algorithms for non-negativity constraints
Algorithms for linear constraints
Solution of the linearly constrained case studies
Algorithms for non-linear constraints
Solution of the non-linearly constrained case studies
References
Index
Appendices
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