| Title of Article |
Multi-surrogate-assisted metaheuristics for crashworthiness optimisation |
| Date of Acceptance |
24 March 2020 |
| Journal |
| Title of Journal |
International Journal of Vehicle Design |
| Standard |
SCOPUS |
| Institute of Journal |
Multi-surrogate-assisted metaheuristics for crashworthiness optimisation |
| ISBN/ISSN |
|
| Volume |
Volume 80 |
| Issue |
Issue 2-4 |
| Month |
September |
| Year of Publication |
2023 |
| Page |
223-240 |
| Abstract |
This work proposes a multi-surrogate-assisted optimisation and
performance investigation of several newly developed metaheuristics (MHs)
for the optimisation of vehicle crashworthiness. The optimisation problem for
car crashworthiness is posed to find the shape and size of a crash box while the
objective function is to maximise the total energy absorption subject to a mass
constraint. Two main numerical experiments are conducted. Firstly, the
performance of different surrogate models along with the proposed multisurrogate model is investigated. Secondly, several MHs are applied to tackle
the proposed crashworthiness optimisation problem by employing the best
obtained surrogate model. The results reveal that the proposed multi-surrogatemodel is the best performer. Among the several MHs used in this study, sine
cosine algorithm is the best algorithm for the proposed multi-surrogate model.
Based on this study, the application of the proposed multi-surrogate model is
better than using one particular traditional surrogate model, especially for
constrained optimisation. |
| Keyword |
surrogate-assisted optimisation; crash box design; evolutionary algorithm; constrained optimisation; meta-heuristics; crashworthiness optimisation; Kriging model |
| Author |
|
| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ตีพิมพ์แล้ว |
| Level of Publication |
นานาชาติ |
| citation |
true |
| Part of thesis |
true |
| Attach file |
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| Citation |
0
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Publication
Journal Publication
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