Applied Optimization: Formulation and Algorithms for Engineering Systems

Applied Optimization: Formulation and Algorithms for Engineering Systems

by Ross Baldick
     
 

ISBN-10: 0521100283

ISBN-13: 9780521100281

Pub. Date: 01/18/2009

Publisher: Cambridge University Press

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

Overview

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.

Product Details

ISBN-13:
9780521100281
Publisher:
Cambridge University Press
Publication date:
01/18/2009
Edition description:
New Edition
Pages:
792
Product dimensions:
6.60(w) x 9.50(h) x 1.80(d)

Table of Contents

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.

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