High-Performance Simulation-Based Optimization

AvThomas Bartz-Beielstein,Bogdan Filipič

Häftad, Engelska, 2020

Del i serien Studies in Computational Intelligence

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Beskrivning

This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations.

Produktinformation

Utgivningsdatum:2020-08-14
Mått:155 x 235 x 17 mm
Vikt:470 g
Format:Häftad
Språk:Engelska
Serie:Studies in Computational Intelligence
Antal sidor:291
Förlag:Springer Nature Switzerland AG
ISBN:9783030187668

Utforska kategorier

Optimering inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

Innehållsförteckning

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.