Novelty particle swarm optimisation for truss optimisation problems

Hirad Assimi; Frank Neumann; Markus Wagner; Xiaodong Li

doi:10.1145/3449726.3459572

Novelty particle swarm optimisation for truss optimisation problems

Hirad Assimi, Frank Neumann, Markus Wagner, Xiaodong Li

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

1 Citation (Scopus)

Abstract

Bilevel optimisation has been successfully applied to truss optimisation to consider topology and sizing in upper and lower levels, respectively. This study proposes novelty particle swarm optimisation for the upper level to discover new designs by maximising novelty. Our experimental investigations show that our approach outperforms current state-of-the-art methods and obtains multiple high-quality solutions.

Original language	English
Title of host publication	Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion
Editors	Krzysztof Krawiec
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	67-68
Number of pages	2
ISBN (Electronic)	9781450383516
DOIs	https://doi.org/10.1145/3449726.3459572
Publication status	Published - 2021
Externally published	Yes
Event	The Genetic and Evolutionary Computation Conference 2021 - Online, Lille, France Duration: 10 Jul 2021 → 14 Jul 2021 Conference number: 23rd https://dl.acm.org/doi/proceedings/10.1145/3449639 (Proceedings)

Conference

Conference	The Genetic and Evolutionary Computation Conference 2021
Abbreviated title	GECCO 2021
Country/Territory	France
City	Lille
Period	10/07/21 → 14/07/21
Internet address	https://dl.acm.org/doi/proceedings/10.1145/3449639 (Proceedings)

Keywords

bilevel optimisation
novelty search
truss

Access to Document

10.1145/3449726.3459572

Cite this

@inproceedings{7c860b06e6fa4fb1a6be5b91a99cfc39,

title = "Novelty particle swarm optimisation for truss optimisation problems",

abstract = "Bilevel optimisation has been successfully applied to truss optimisation to consider topology and sizing in upper and lower levels, respectively. This study proposes novelty particle swarm optimisation for the upper level to discover new designs by maximising novelty. Our experimental investigations show that our approach outperforms current state-of-the-art methods and obtains multiple high-quality solutions.",

keywords = "bilevel optimisation, novelty search, truss",

author = "Hirad Assimi and Frank Neumann and Markus Wagner and Xiaodong Li",

note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; The Genetic and Evolutionary Computation Conference 2021, GECCO 2021 ; Conference date: 10-07-2021 Through 14-07-2021",

year = "2021",

doi = "10.1145/3449726.3459572",

language = "English",

pages = "67--68",

editor = "Krzysztof Krawiec",

booktitle = "Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

url = "https://dl.acm.org/doi/proceedings/10.1145/3449639",

}

Assimi, H, Neumann, F, Wagner, M & Li, X 2021, Novelty particle swarm optimisation for truss optimisation problems. in K Krawiec (ed.), Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery (ACM), New York NY USA, pp. 67-68, The Genetic and Evolutionary Computation Conference 2021, Lille, France, 10/07/21. https://doi.org/10.1145/3449726.3459572

Novelty particle swarm optimisation for truss optimisation problems. / Assimi, Hirad; Neumann, Frank; Wagner, Markus et al.
Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. ed. / Krzysztof Krawiec. New York NY USA: Association for Computing Machinery (ACM), 2021. p. 67-68.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

TY - GEN

T1 - Novelty particle swarm optimisation for truss optimisation problems

AU - Assimi, Hirad

AU - Neumann, Frank

AU - Wagner, Markus

AU - Li, Xiaodong

N1 - Conference code: 23rd

PY - 2021

Y1 - 2021

N2 - Bilevel optimisation has been successfully applied to truss optimisation to consider topology and sizing in upper and lower levels, respectively. This study proposes novelty particle swarm optimisation for the upper level to discover new designs by maximising novelty. Our experimental investigations show that our approach outperforms current state-of-the-art methods and obtains multiple high-quality solutions.

AB - Bilevel optimisation has been successfully applied to truss optimisation to consider topology and sizing in upper and lower levels, respectively. This study proposes novelty particle swarm optimisation for the upper level to discover new designs by maximising novelty. Our experimental investigations show that our approach outperforms current state-of-the-art methods and obtains multiple high-quality solutions.

KW - bilevel optimisation

KW - novelty search

KW - truss

UR - http://www.scopus.com/inward/record.url?scp=85111051415&partnerID=8YFLogxK

U2 - 10.1145/3449726.3459572

DO - 10.1145/3449726.3459572

M3 - Conference Paper

AN - SCOPUS:85111051415

SP - 67

EP - 68

BT - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion

A2 - Krawiec, Krzysztof

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

T2 - The Genetic and Evolutionary Computation Conference 2021

Y2 - 10 July 2021 through 14 July 2021

ER -

Novelty particle swarm optimisation for truss optimisation problems

Abstract

Conference

Keywords

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