Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Derivative-free DIRECT-type Global Optimization

Applications and Software
BuchKartoniert, Paperback
122 Seiten
Englisch
Springererschienen am28.11.20231st ed. 2023
Lastly, the authors demonstrate the performance of the algorithms for solving a wide range of global optimization problems with various constraints ranging from a few to hundreds of variables.Additionally, well-known practical problems from the literature are used to demonstrate the effectiveness of the developed algorithms.mehr
Verfügbare Formate
BuchGebunden
EUR48,14
BuchKartoniert, Paperback
EUR48,14
E-BookPDF1 - PDF WatermarkE-Book
EUR48,14

Produkt

KlappentextLastly, the authors demonstrate the performance of the algorithms for solving a wide range of global optimization problems with various constraints ranging from a few to hundreds of variables.Additionally, well-known practical problems from the literature are used to demonstrate the effectiveness of the developed algorithms.
Details
ISBN/GTIN978-3-031-46539-0
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2023
Erscheinungsdatum28.11.2023
Auflage1st ed. 2023
ReiheSpringerBriefs in Optimization
Seiten122 Seiten
SpracheEnglisch
IllustrationenX, 122 p. 43 illus., 39 illus. in color.
Artikel-Nr.55681463

Inhalt/Kritik

Inhaltsverzeichnis
Preface.- Chapter. 1. The Role of the DIRECT Algorithm in Derivative-Free Global Optimization.- Chapter. 2. Development of DIRECT-Type Algorithms.- Chapter. 3. Applications and Software.mehr

Schlagworte

Autor

Linas Stripinis received a Ph.D. degree in informatics from Vilnius University, Lithuania, in 2021. He is currently a researcher at Vilnius University. His research interests include global optimization, optimization software, parallel computing, and machine learning techniques.
Remigijus Paulavicius received a Ph.D. degree in computer science from Vytautas Magnus University, Lithuania, in 2010. He was a Postdoctoral Researcher at Vilnius University, Lithuania, and a Research Associate at Imperial College London, UK. Since 2019, he has been a member of the Young Academy of the Lithuanian Academy of Sciences and a professor of informatics at the Institute of Data Science and Digital Technologies of Vilnius University. His research interests include global optimization, optimization software, parallel and quantum computing, and distributed ledger technologies.
Weitere Artikel von
Stripinis, Linas