SMWO/D: a decomposition-based switching multi-objective whale optimiser for structural optimisation of Turbine disk in aero-engines

In this paper, a novel multidisciplinary design optimisation (MDO) algorithm is proposed, which is named as the decomposition-based switching multi-objective whale optimiser (SMWO/D). In particular, a penalty-Tchebycheff value-based decomposition framework is designed to decouple the strongly correl...

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Bibliographic Details
Published in:International journal of systems science Vol. 54; no. 8; pp. 1713 - 1728
Main Authors: Li, Han, Liu, Haonan, Lan, Chengbo, Yin, Yiqi, Wu, Peishu, Yan, Cheng, Zeng, Nianyin
Format: Journal Article
Language:English
Published: London Taylor & Francis 11.06.2023
Taylor & Francis Ltd
Subjects:
aero-engine
Aerospace engines
Algorithms
Decomposition
multi-objective optimisation algorithm (MOA)
Multidisciplinary design optimisation (MDO)
Multidisciplinary design optimization
Multiple objective analysis
Parameter sensitivity
Sensitivity analysis
structural optimisation
Switching
Turbine disks
Whales
ISSN:0020-7721, 1464-5319
Online Access:Get full text
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Summary:In this paper, a novel multidisciplinary design optimisation (MDO) algorithm is proposed, which is named as the decomposition-based switching multi-objective whale optimiser (SMWO/D). In particular, a penalty-Tchebycheff value-based decomposition framework is designed to decouple the strongly correlated conflicting objectives, so as to give comprehensive considerations to different disciplinary demands. To overcome the shortcoming of premature in the complicated multi-modal non-linear decision space, two adaptively switchable evolutionary modes are defined to enhance the ability of escaping from local optimum and promote a thorough global search with rich learning strategies. The proposed SMWO/D is evaluated on a series of benchmark functions, and the results show its competitiveness in terms of comprehensive performance as compared with other four popular decomposition-based multi-objective optimisation algorithms (MOAs). In addition, sensitivity analysis is carried out to determine the best parameter configuration of SMWO/D. Finally, in a case study of a real-world turbine disk structural optimisation, the practicality of the proposed SMWO/D is validated, which can effectively handle the multidisciplinary property of this complicated problem, thereby providing valuable experiences in the aero-engine MDO domain.
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ISSN:0020-7721
1464-5319
DOI:10.1080/00207721.2023.2209873