Derivative-Free and Blackbox Optimization [[electronic resource] /] / by Charles Audet, Warren Hare

• Autore: Audet Charles
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
• Edizione: 1st ed. 2017.
• Descrizione fisica: 1 online resource (XVIII, 302 p. 38 illus.)
• Disciplina: 519.3
• Soggetto topico: Mathematical optimization; Numerical analysis; Optimization; Numerical Analysis
• Persona (resp. second.): HareWarren
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Derivative-Free and Blackbox Optimization
• ISBN: 3-319-68913-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910254294603321
• Lo trovi qui: Univ. Federico II
• Serie: Springer Series in Operations Research and Financial Engineering, . 1431-8598