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Infill sampling criteria for surrogate-based optimization with constraint handling

Infill sampling criteria for surrogate-based optimization with constraint handling
Infill sampling criteria for surrogate-based optimization with constraint handling
This article discusses the benefits of different infill sampling criteria used in surrogate-based constrained global optimization. A new method which selects multiple updates based on Pareto optimal solutions is introduced showing improvements over a number of existing methods. The construction of surrogates (also known as meta-models or response surface models) involves the selection of a limited number of designs which are analysed using the original expensive functions. A typical approach involves two stages. First the surrogate is built using an initial sampling plan; the second stage updates the model using an infill sampling criterion to select further designs that offer improvement. Selecting multiple update points at each iteration, allowing distribution of the expensive function evaluations on several processors offers large potential for accelerating the overall optimization process. This article provides a comparison between different infill sampling criteria suitable for selecting multiple update points in the presence of constraints.
1147-1166
Parr, James
7ca0b05c-1ef7-433f-aa21-342cafc95eb5
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Forrester, A.I.J.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
Holden, C.M.E.
66fd6373-7d88-48e3-9d86-4a74421db4da
Parr, James
7ca0b05c-1ef7-433f-aa21-342cafc95eb5
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Forrester, A.I.J.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
Holden, C.M.E.
66fd6373-7d88-48e3-9d86-4a74421db4da

Parr, James, Keane, A.J., Forrester, A.I.J. and Holden, C.M.E. (2012) Infill sampling criteria for surrogate-based optimization with constraint handling. Engineering Optimization, 44 (10), 1147-1166. (doi:10.1080/0305215X.2011.637556).

Record type: Article

Abstract

This article discusses the benefits of different infill sampling criteria used in surrogate-based constrained global optimization. A new method which selects multiple updates based on Pareto optimal solutions is introduced showing improvements over a number of existing methods. The construction of surrogates (also known as meta-models or response surface models) involves the selection of a limited number of designs which are analysed using the original expensive functions. A typical approach involves two stages. First the surrogate is built using an initial sampling plan; the second stage updates the model using an infill sampling criterion to select further designs that offer improvement. Selecting multiple update points at each iteration, allowing distribution of the expensive function evaluations on several processors offers large potential for accelerating the overall optimization process. This article provides a comparison between different infill sampling criteria suitable for selecting multiple update points in the presence of constraints.

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Published date: 2012
Organisations: Computational Engineering & Design Group

Identifiers

Local EPrints ID: 345632
URI: http://eprints.soton.ac.uk/id/eprint/345632
PURE UUID: a7902ef4-f1ed-4002-82cf-4afaf532d559
ORCID for A.J. Keane: ORCID iD orcid.org/0000-0001-7993-1569

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Date deposited: 27 Nov 2012 14:43
Last modified: 15 Mar 2024 02:52

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Contributors

Author: James Parr
Author: A.J. Keane ORCID iD
Author: C.M.E. Holden

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