عنوان

High-Performance Simulation-Based Optimization /

شابک

3030187640

شابک

9783030187644

شابک اشتباه

3030187632

شابک اشتباه

9783030187637

عنوان اصلي

High-Performance Simulation-Based Optimization /

نام عام مواد

[Book]

نام نخستين پديدآور

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

محل نشرو پخش و غیره

Cham :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

2020.

نام خاص و کميت اثر

1 online resource (xiii, 291 pages) :

ساير جزييات

illustrations (some color)

عنوان فروست

Studies in computational intelligence ;

مشخصه جلد

volume 833

متن يادداشت

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.

بدون عنوان

0

متن يادداشت

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.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030187644

عنوان

High-Performance Simulation-Based Optimization.

شماره استاندارد بين المللي کتاب و موسيقي

9783030187637

موضوع مستند نشده

Mathematical optimization.

موضوع مستند نشده

Simulation methods.

موضوع مستند نشده

Mathematical optimization.

موضوع مستند نشده

Simulation methods.

شماره

شماره رده

مستند نام اشخاص تاييد نشده

Bartz-Beielstein, Thomas.

مستند نام اشخاص تاييد نشده

Filipič, Bogdan.

مستند نام اشخاص تاييد نشده

Korošec, Peter.

مستند نام اشخاص تاييد نشده

Talbi, El-Ghazali.

تاريخ عمليات

20200823090504.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y