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Derivative-Free and Blackbox Optimization
ISBN-13:
9783319689135
Veröffentl:
2017
Seiten:
302
Autor:
Charles Audet
Serie:
Springer Series in Operations Research and Financial Engineering
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
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.
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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