Applied Optimization

Formulation and Algorithms for Engineering Systems

Häftad, Engelska, 2009

Av Ross Baldick, Austin) Baldick, Ross (University of Texas, Baldick Ross

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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.

Produktinformation

Utgivningsdatum2009-01-18
Mått170 x 244 x 40 mm
Vikt1 240 g
FormatHäftad
SpråkEngelska
Antal sidor792
FörlagCambridge University Press
ISBN9780521100281

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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; 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.