High-Performance Simulation-Based Optimization
Springer International Publishing (Verlag)
978-3-030-18763-7 (ISBN)
Infill Criteria for Multiobjective Bayesian Optimization.- Many-Objective Optimization with Limited Computing Budget.- Multi-Objective Bayesian Optimization for Engineering Simulation.- Automatic Configuration of Multi-Objective Optimizers and Multi-Objective Configuration.- Optimization and Visualization in Many-Objective Space Trajectory Design.- Simulation Optimization through Regression or Kriging Metamodels.- Towards Better Integration of Surrogate Models and Optimizers.- Surrogate-Assisted Evolutionary Optimization of Large Problems.- Overview and Comparison of Gaussian Process-Based Surrogate Models for Mixed Continuous and Discrete Variables: Application on Aerospace Design Problems.- Open Issues in Surrogate-Assisted Optimization.- A Parallel Island Model for Hypervolume-Based Many-Objective Optimization.- Many-Core Branch-and-Bound for GPU Accelerators and MIC Coprocessors.
Erscheinungsdatum | 16.06.2019 |
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Reihe/Serie | Studies in Computational Intelligence |
Zusatzinfo | XIII, 291 p. 71 illus., 47 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 619 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Technik ► Elektrotechnik / Energietechnik | |
Schlagworte | Computational Intelligence • High-performance Algorithms • machine learning • Many-Objective Optimization • parallel optimization • surrogate-based optimization |
ISBN-10 | 3-030-18763-2 / 3030187632 |
ISBN-13 | 978-3-030-18763-7 / 9783030187637 |
Zustand | Neuware |
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