Self-adaptive many-objective meta-heuristic based on decomposition for many-objective conceptual design of a fixed wing unmanned aerial vehicle
Many-objective optimisation is a design problem, having more than 3 objective functions, which is found to be difficult to solve. Implementation of such optimisation on aircraft conceptual design will greatly benefit a design team, as a great number of trade-off design solutions are provided for fur...
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| Published in | Aerospace science and technology Vol. 100; p. 105783 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Masson SAS
01.05.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1270-9638 1626-3219 |
| DOI | 10.1016/j.ast.2020.105783 |
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| Abstract | Many-objective optimisation is a design problem, having more than 3 objective functions, which is found to be difficult to solve. Implementation of such optimisation on aircraft conceptual design will greatly benefit a design team, as a great number of trade-off design solutions are provided for further decision making. In this paper, a many-objective optimisation problem for an unmanned aerial vehicle (UAV) is posed with 6 objective functions: take-off gross weight, drag coefficient, take off distance, power required, lift coefficient and endurance subject to aircraft performance and stability constraints. Aerodynamic analysis is carried out using a vortex lattice method, while aircraft component weights are estimated empirically. A new self-adaptive meta-heuristic based on decomposition is specifically developed for this design problem. The new algorithm along with nine established and recently developed multi-objective and many-objective meta-heuristics are employed to solve the problem, while comparative performance is made based upon a hypervolume indicator. The results reveal that the proposed optimiser is the best performer for this design task. |
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| AbstractList | Many-objective optimisation is a design problem, having more than 3 objective functions, which is found to be difficult to solve. Implementation of such optimisation on aircraft conceptual design will greatly benefit a design team, as a great number of trade-off design solutions are provided for further decision making. In this paper, a many-objective optimisation problem for an unmanned aerial vehicle (UAV) is posed with 6 objective functions: take-off gross weight, drag coefficient, take off distance, power required, lift coefficient and endurance subject to aircraft performance and stability constraints. Aerodynamic analysis is carried out using a vortex lattice method, while aircraft component weights are estimated empirically. A new self-adaptive meta-heuristic based on decomposition is specifically developed for this design problem. The new algorithm along with nine established and recently developed multi-objective and many-objective meta-heuristics are employed to solve the problem, while comparative performance is made based upon a hypervolume indicator. The results reveal that the proposed optimiser is the best performer for this design task. |
| ArticleNumber | 105783 |
| Author | Yildiz, Ali Riza Bureerat, Sujin Pholdee, Nantiwat Panagant, Natee Champasak, Pakin |
| Author_xml | – sequence: 1 givenname: Pakin surname: Champasak fullname: Champasak, Pakin organization: Sustainable Infrastructure Research and Development Centre, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, 40002, Thailand – sequence: 2 givenname: Natee surname: Panagant fullname: Panagant, Natee organization: Sustainable Infrastructure Research and Development Centre, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, 40002, Thailand – sequence: 3 givenname: Nantiwat surname: Pholdee fullname: Pholdee, Nantiwat organization: Sustainable Infrastructure Research and Development Centre, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, 40002, Thailand – sequence: 4 givenname: Sujin surname: Bureerat fullname: Bureerat, Sujin email: sujbur@kku.ac.th organization: Sustainable Infrastructure Research and Development Centre, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, 40002, Thailand – sequence: 5 givenname: Ali Riza surname: Yildiz fullname: Yildiz, Ali Riza organization: Department of Automotive Engineering, Bursa Uludağ University, Görükle, Bursa, Turkey |
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