| Title of Article |
Multiobjective meta-heuristic with iterative parameter distribution estimation for aeroelastic design of an aircraft wing |
| Date of Acceptance |
26 May 2020 |
| Journal |
| Title of Journal |
Engineering with Computers |
| Standard |
ISI |
| Institute of Journal |
Springer-Verlag London Ltd. |
| ISBN/ISSN |
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| Volume |
|
| Issue |
|
| Month |
June |
| Year of Publication |
2020 |
| Page |
https://doi.org/10.1007/s00366-020-01077-w |
| Abstract |
This paper proposes a new self-adaptive meta-heuristic (MH) algorithm for multiobjective optimisation. The adaptation is accomplished by means of estimation of distribution. The differential evolution reproduction strategy is modified and used in this dominance-based multiobjective optimiser whereas population-based incremental learning is used to estimate the control parameters. The new method is employed to solve aeroelastic multiobjective optimisation of an aircraft wing which optimises structural weight and flutter speed. Design variables in the aeroelastic design problem include thicknesses of ribs, spars and composite layers. Also, the ply orientation of the upper and lower composite skins are assigned as the design variables. Additional benchmark test problems are also use to validate the search performance of the proposed algorithm. The performance validation reveals that the proposed optimiser is among the state-of-the-art multiobjective meta-heuristics. The concept of using estimation of distribution algorithm for tuning meta-heuristic control parameters is efficient and effective and becomes a new direction for improving MH performance. |
| Keyword |
Aeroelasticity · Aircraft wing · Surrogate models · Multiobjective evolutionary algorithms · Estimation of distribution algorithm |
| Author |
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| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ตีพิมพ์แล้ว |
| Level of Publication |
นานาชาติ |
| citation |
false |
| Part of thesis |
true |
| Attach file |
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| Citation |
0
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Publication
Journal Publication
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