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Localized probability of improvement for kriging based multi-objective optimization

Localized probability of improvement for kriging based multi-objective optimization
Localized probability of improvement for kriging based multi-objective optimization
The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.
Kriging, Multi-Objective Optimization, Pareto front, Surrogate-based optimization
2391-5471
954-958
Li, Yinjiang
035e8693-c6e6-4a91-8e10-9232fd0c3112
Xiao, Song
6ffa9657-513e-4b86-86a2-e560d3c09c72
Di Barba, Paolo
2a71a034-4c2a-4e74-9e8f-9ccd7fa88104
Rotaru, Mihai
c53c5038-2fed-4ace-8fad-9f95d4c95b7e
Sykulski, Jan
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Li, Yinjiang
035e8693-c6e6-4a91-8e10-9232fd0c3112
Xiao, Song
6ffa9657-513e-4b86-86a2-e560d3c09c72
Di Barba, Paolo
2a71a034-4c2a-4e74-9e8f-9ccd7fa88104
Rotaru, Mihai
c53c5038-2fed-4ace-8fad-9f95d4c95b7e
Sykulski, Jan
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb

Li, Yinjiang, Xiao, Song, Di Barba, Paolo, Rotaru, Mihai and Sykulski, Jan (2017) Localized probability of improvement for kriging based multi-objective optimization. Open Physics, 15 (1), 954-958. (doi:10.1515/phys-2017-0117).

Record type: Article

Abstract

The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.

Text
Open Physics 2017 page 954-958 - Version of Record
Available under License Creative Commons Attribution.
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More information

Accepted/In Press date: 12 November 2017
Published date: 29 December 2017
Related URLs:
Keywords: Kriging, Multi-Objective Optimization, Pareto front, Surrogate-based optimization
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Identifiers

Local EPrints ID: 417582
URI: http://eprints.soton.ac.uk/id/eprint/417582
DOI: doi:10.1515/phys-2017-0117
ISSN: 2391-5471
PURE UUID: 44247b90-c98b-42d8-86fe-d5516fafbdd6
ORCID for Jan Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

Catalogue record

Date deposited: 05 Feb 2018 17:30
Last modified: 16 Mar 2024 02:34

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Contributors

Author: Yinjiang Li
Author: Song Xiao
Author: Paolo Di Barba
Author: Mihai Rotaru
Author: Jan Sykulski ORCID iD

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