GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
type: Item
instance of: scholarly article
title: GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
zbMATH Open document ID: 1478.90098
author: Yanyan Li
published in: Optimization and Engineering
publication date: 2022-01-20T00:00:00Z
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 90C56
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 7460654
zbMATH Keywords: PDE-constrained optimization
zbMATH Keywords: surrogate models
zbMATH Keywords: parallel computing
zbMATH Keywords: water quality models
zbMATH Keywords: global optimization
zbMATH Keywords: multi-modal and black-box objective
describes a project that uses: ELCOM
describes a project that uses: Delft3D-WAQ
describes a project that uses: MultiMin
describes a project that uses: MISO
describes a project that uses: MIKE SHE
describes a project that uses: MPI
describes a project that uses: EGO
describes a project that uses: pySOT
describes a project that uses: NOMAD
describes a project that uses: MLMSRBF
MaRDI profile type: Publication
full work available at URL: s11081-020-09556-1
OpenAlex ID: W3094493444
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DOI: 10.1007/S11081-020-09556-1
description: scientific article; zbMATH DE number 7460654