Articles liés à Evolutionary Multiobjective Optimization with Gaussian...
Synopsis
This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions.
Biographie de l'auteur
Miha Mlakar finished his Ph.D. in Information and Communication Technologies from the Jožef Stefan International Postgraduate School in Ljubljana, Slovenia.He is currently working as a Postdoctoral Associate at Jožef Stefan Insitute, focusing on evolutionary algorithms, optimization, machine learning, data science and industrial applications.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurLAP LAMBERT Academic Publishing
- Date d'édition2015
- ISBN 10 365975935X
- ISBN 13 9783659759352
- ReliureBroché
- Langueanglais
- Nombre de pages116
- Coordonnées du fabricantnon disponible
Acheter neuf
Afficher cet article
EUR 45,45
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisRésultats de recherche pour Evolutionary Multiobjective Optimization with Gaussian...
Image fournie par le vendeur
Evolutionary Multiobjective Optimization with Gaussian Process Models
Edité par
LAP LAMBERT Academic Publishing, 2015
ISBN 10 : 365975935X
ISBN 13 : 9783659759352
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 158247459
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Evolutionary Multiobjective Optimization with Gaussian Process Models
Edité par
LAP LAMBERT Academic Publishing Jul 2015, 2015
ISBN 10 : 365975935X
ISBN 13 : 9783659759352
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions. 116 pp. Englisch. N° de réf. du vendeur 9783659759352
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Evolutionary Multiobjective Optimization with Gaussian Process Models
Edité par
LAP LAMBERT Academic Publishing, 2015
ISBN 10 : 365975935X
ISBN 13 : 9783659759352
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions. N° de réf. du vendeur 9783659759352
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Evolutionary Multiobjective Optimization with Gaussian Process Models
Edité par
LAP LAMBERT Academic Publishing Jul 2015, 2015
ISBN 10 : 365975935X
ISBN 13 : 9783659759352
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch. N° de réf. du vendeur 9783659759352
Quantité disponible : 1 disponible(s)
Image d'archives
Evolutionary Multiobjective Optimization with Gaussian Process Models
Edité par
LAP LAMBERT Academic Publishing, 2015
ISBN 10 : 365975935X
ISBN 13 : 9783659759352
Ancien ou d'occasion
paperback
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
paperback. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA800365975935X6
Quantité disponible : 1 disponible(s)