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Viser: Derivative-Free and Blackbox Optimization

Derivative-Free and Blackbox Optimization
Søgbar e-bog

Derivative-Free and Blackbox Optimization Vital Source e-bog

Charles Audet
(2017)
Springer Nature
634,00 kr.
Leveres umiddelbart efter køb
Derivative-Free and Blackbox Optimization

Derivative-Free and Blackbox Optimization Vital Source e-bog

Charles Audet og Warren Hare
(2017)
Springer Nature
317,00 kr.
Leveres umiddelbart efter køb
Derivative-Free and Blackbox Optimization

Derivative-Free and Blackbox Optimization Vital Source e-bog

Charles Audet og Warren Hare
(2017)
Springer Nature
412,00 kr.
Leveres umiddelbart efter køb
Derivative-Free and Blackbox Optimization

Derivative-Free and Blackbox Optimization

Charles Audet og Warren Hare
(2017)
Sprog: Engelsk
Springer International Publishing AG
1.033,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.

Detaljer om varen

  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: Springer Nature (December 2017)
  • ISBN: 9783319689135
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization.  The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I.  Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead).  Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region).  Part V discusses dealing with constraints, using surrogates, and bi-objective optimization. End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures.  Benchmarking techniques are also presented in the appendix.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • Vital Source 90 day rentals (dynamic pages)
  • Udgiver: Springer Nature (December 2017)
  • Forfattere: Charles Audet og Warren Hare
  • ISBN: 9783319689135R90
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization.  The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I.  Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead).  Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region).  Part V discusses dealing with constraints, using surrogates, and bi-objective optimization. End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures.  Benchmarking techniques are also presented in the appendix.
Licens varighed:
Bookshelf online: 90 dage fra købsdato.
Bookshelf appen: 90 dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • Vital Source 180 day rentals (dynamic pages)
  • Udgiver: Springer Nature (December 2017)
  • Forfattere: Charles Audet og Warren Hare
  • ISBN: 9783319689135R180
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization.  The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I.  Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead).  Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region).  Part V discusses dealing with constraints, using surrogates, and bi-objective optimization. End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures.  Benchmarking techniques are also presented in the appendix.
Licens varighed:
Bookshelf online: 180 dage fra købsdato.
Bookshelf appen: 180 dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • Hardback
  • Udgiver: Springer International Publishing AG (December 2017)
  • Forfattere: Charles Audet og Warren Hare
  • ISBN: 9783319689128

This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization. 

The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I.  Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead).  Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region).  Part V discusses dealing with constraints, using surrogates, and bi-objective optimization.

End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures.  Benchmarking techniques are also presented in the appendix.


Part I: Introduction and Background Material.- Introduction: Tools and Challenges.- Mathematical Background.- The Beginnings of DFO Algorithms.-
Part I: Some Remarks on DFO.-
Part II: Popular Heuristic Methods.- Genetic Algorithms.- Nelder-Mead.-
Part II: Further Remarks on Heuristics.-
Part III: Direct Search Methods.- Positive bases and Nonsmooth Optimization.- Generalized Pattern Search.- Mesh Adaptive Direct Search.-
Part III: Further Remarks on Direct Search Methods.-
Part IV: Model-based Methods.- Model-based Descent.- Model-based Trust Region.-
Part IV: Further Remarks on Model-based Methods.-
Part V: Extensions and Refinements.- Variables and Constraints.- Optimization Using Surrogates and Models.- Biobjective Optimization.-
Part V: Final Remarks on DFO/BBO.-
Part VI: Appendix: Comparing Optimization Methods.- Solutions to Selected Exercises.
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