GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration

10.1007/s11081-020-09556-1

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Bibliographic Details
Main Authors:	Xia, Wei, Shoemaker, Christine
Other Authors:	INDUSTRIAL SYSTEMS ENGINEERING AND MANAGEMENT
Format:	Article
Published:	Springer 2022
Subjects:	Global optimization Multi-modal and black-box objective Parallel computing PDE-constrained optimization Surrogate models Water quality models
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/232578
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-232578
record_format	dspace
spelling	sg-nus-scholar.10635-2325782024-04-05T02:08:52Z GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration Xia, Wei Shoemaker, Christine INDUSTRIAL SYSTEMS ENGINEERING AND MANAGEMENT Global optimization Multi-modal and black-box objective Parallel computing PDE-constrained optimization Surrogate models Water quality models 10.1007/s11081-020-09556-1 Optimization and Engineering 22 4 2741-2777 2022-10-12T08:14:19Z 2022-10-12T08:14:19Z 2020-09-17 Article Xia, Wei, Shoemaker, Christine (2020-09-17). GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration. Optimization and Engineering 22 (4) : 2741-2777. ScholarBank@NUS Repository. https://doi.org/10.1007/s11081-020-09556-1 1389-4420 https://scholarbank.nus.edu.sg/handle/10635/232578 Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ Springer Scopus OA2021
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Global optimization Multi-modal and black-box objective Parallel computing PDE-constrained optimization Surrogate models Water quality models
spellingShingle	Global optimization Multi-modal and black-box objective Parallel computing PDE-constrained optimization Surrogate models Water quality models Xia, Wei Shoemaker, Christine GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
description	10.1007/s11081-020-09556-1
author2	INDUSTRIAL SYSTEMS ENGINEERING AND MANAGEMENT
author_facet	INDUSTRIAL SYSTEMS ENGINEERING AND MANAGEMENT Xia, Wei Shoemaker, Christine
format	Article
author	Xia, Wei Shoemaker, Christine
author_sort	Xia, Wei
title	GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
title_short	GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
title_full	GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
title_fullStr	GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
title_full_unstemmed	GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
title_sort	gops: efficient rbf surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality pde model calibration
publisher	Springer
publishDate	2022
url	https://scholarbank.nus.edu.sg/handle/10635/232578
_version_	1800915622304940032

GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration

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