Linear and Nonlinear Optimization

Name: Linear and Nonlinear Optimization
Brand: CAMBRIDGE UNIVERSITY PRESS
SKU: 401204
Price: 78.95 EUR
Availability: InStock

IGOR GRIVA

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78,95 €

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ISBN

9780898716610

Mladinska knjiga ID

401204

Leto izida

2009

Datum izida

28.02.2009

Velikost (šxdxv)

150 × 200 × 10

Status dobavljivosti

Na zalogi pri dobavitelju

Jezik

ANG

Založnik

CAMBRIDGE UNIVERSITY PRESS

Avtor

IGOR GRIVA

Opis

Flexible graduate textbook that introduces the applications, theory, and algorithms of linear and nonlinear optimization.Provides an introduction to the applications, theory, and algorithms of linear and nonlinear optimization. The emphasis is on practical aspects - discussing modern algorithms, as well as the influence of theory on the interpretation of solutions or on the design of software. The book includes several examples of realistic optimization models that address important applications. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. The book is designed to be flexible. It has a modular structure, and uses consistent notation and terminology throughout. It can be used in many different ways, in many different courses, and at many different levels of sophistication.Preface; Part I. Basics: 1. Optimization models; 2. Fundamentals of optimization; 3. Representation of linear constraints; Part II. Linear Programming: 4. Geometry of linear programming; 5. The simplex method; 6. Duality and sensitivity; 7. Enhancements of the simplex method; 8. Network problems; 9. Computational complexity of linear programming; 10. Interior-point methods of linear programming; Part III. Unconstrained Optimization: 11. Basics of unconstrained optimization; 12. Methods for unconstrained optimization; 13. Low-storage methods for unconstrained problems; Part IV. Nonlinear Optimization: 14. Optimality conditions for constrained problems; 15. Feasible-point methods; 16. Penalty and barrier methods; Part V. Appendices: Appendix A. Topics from linear algebra; Appendix B. Other fundamentals; Appendix C. Software; Bibliography; Index.