MVMOO: mixed variable multi-objective optimisation
type: Item
instance of: scholarly article
title: MVMOO: mixed variable multi-objective optimisation
zbMATH Open document ID: 1475.90094
author: Jamie A. Manson
author: Thomas W. Chamberlain
author: Richard A. Bourne
published in: Journal of Global Optimization
publication date: 2021-08-17T00:00:00Z
Mathematics Subject Classification ID: 90C29
Mathematics Subject Classification ID: 90C11
zbMATH DE Number: 7382684
zbMATH Keywords: global optimisation
zbMATH Keywords: hypervolume
zbMATH Keywords: multi-objective
zbMATH Keywords: mixed variable
zbMATH Keywords: Bayesian optimisation
describes a project that uses: jMetalPy
describes a project that uses: DFVLR-SQP
describes a project that uses: SciPy
describes a project that uses: TensorFlow
describes a project that uses: GPflow
describes a project that uses: Python
MaRDI profile type: Publication
full work available at URL: s10898-021-01052-9
OpenAlex ID: W3177619992
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cites work: Expected improvement for expensive optimization: a review
cites work: Q3394879
cites work: Q5361306
cites work: Q3790948
cites work: A family of embedded Runge-Kutta formulae
DOI: 10.1007/S10898-021-01052-9
description: scientific article; zbMATH DE number 7382684