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Applied Optimization: Formulation and Algorithms for Engineering Systems by Ross

Product Details
 
Synopsis
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, the 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. Book jacket.


Product Identifiers
ISBN-10
0521100283
ISBN-13
9780521100281

Key Details
Author
Ross Baldick
Number Of Pages
792 pages
Format
ebook
Publication Date
2009-01-18
Language
English
Publisher
Cambridge University Press
Publication Year
20090000


Additional Details
Copyright Date
2009
Illustrated
Yes


Dimensions
Weight
43.7 Oz
Height
1.6 In.
Width
6.7 In.
Length
9.6 In.


Target Audience
Group
Scholarly & Professional


Classification Method
LC Classification Number
TA168
Dewey Decimal
620.0011
Dewey Edition
22


Table Of Content
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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