عنوان

High-Performance Simulation-Based Optimization /

(Number (ISBN

3030187640

(Number (ISBN

9783030187644

Erroneous ISBN

3030187632

Erroneous ISBN

9783030187637

Title Proper

High-Performance Simulation-Based Optimization /

General Material Designation

[Book]

First Statement of Responsibility

Thomas Bartz-Beielstein, Bogdan Filipič, Peter Korošec, El-Ghazali Talbi, editors.

Place of Publication, Distribution, etc.

Cham :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

2020.

Specific Material Designation and Extent of Item

1 online resource (xiii, 291 pages) :

Other Physical Details

illustrations (some color)

Series Title

Studies in computational intelligence ;

Volume Designation

volume 833

Text of Note

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.

0

Text of Note

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. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. Thats where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9783030187644

Title

High-Performance Simulation-Based Optimization.

International Standard Book Number

9783030187637

Mathematical optimization.

Simulation methods.

Mathematical optimization.

Simulation methods.

Number

Class number

Bartz-Beielstein, Thomas.

Filipič, Bogdan.

Korošec, Peter.

Talbi, El-Ghazali.

Date of Transaction

20200823090504.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y