High-Performance Simulation-Based Optimization

Häftad, Engelska, 2020

Av Thomas Bartz-Beielstein, Bogdan Filipič, Peter Korošec, El-Ghazali Talbi, Bogdan Filipic, Peter Korosec, Bogdan Filipič, Bogdan Filipi¿, Peter Koro¿ec

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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

Utgivningsdatum2020-08-14
Mått155 x 235 x 17 mm
Vikt470 g
FormatHäftad
SpråkEngelska
SerieStudies in Computational Intelligence
Antal sidor291
FörlagSpringer Nature Switzerland AG
ISBN9783030187668

Tillhör följande kategorier

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.