| Interactive Multi-objective Optimization Design for the Pylon Structure of an Airplane |
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| 作者姓名： | An Weigang Li Weiji |
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| 作者单位： | College of Aeronautics, Northwestern Polytechnical University, Xi ＇an 710072, China |
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| 摘 要： | The pylon structure of an airplane is very complex, and its high-fidelity analysis is quite time-consuming. If posterior preference optimization algorithm is used to solve this problem, the huge time consumption will be unacceptable in engineering practice due to the large amount of evaluation needed for the algorithm. So, a new interactive optimization algorithm-interactive multi-objective particle swarm optimization （IMOPSO） is presented. IMOPSO is efficient, simple and operable. The decision-maker can expediently determine the accurate preference in IMOPSO. IMOPSO is used to perform the pylon structure optimization design of an airplane, and a satisfactory design is achieved after only 12 generations of IMOPSO evolutions. Compared with original design, the maximum displacement of the satisfactory design is reduced, and the mass of the satisfactory design is decreased for 22%.
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| 关 键 词： | 塔门构造 飞机 最佳化设计 技术性能 |
| 收稿时间： | 2007-05-16 |
| 修稿时间： | 2007-09-13 |
Interactive Multi-objective Optimization Design for the Pylon Structure of an Airplane |
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| An Weigang Li Weiji.Interactive Multi-objective Optimization Design for the Pylon Structure of an Airplane[J].Chinese Journal of Aeronautics,2007,20(6):524-528. |
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| Authors: | An Li Weiji |
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| Institution: | aCollege of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China |
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| Abstract: | The pylon structure of an airplane is very complex, and its high-fidelity analysis is quite time-consuming. If posterior preference optimization algorithm is used to solve this problem, the huge time consumption will be unacceptable in engineering practice due to the large amount of evaluation needed for the algorithm. So, a new interactive optimization algorithm-interactive multi-objective particle swarm optimization (IMOPSO) is presented. IMOPSO is efficient, simple and operable. The decision-maker can expediently determine the accurate preference in IMOPSO. IMOPSO is used to perform the pylon structure optimization design of an airplane, and a satisfactory design is achieved after only 12 generations of IMOPSO evolutions. Compared with original design, the maximum displacement of the satisfactory design is reduced, and the mass of the satisfactory design is decreased for 22%. |
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| Keywords: | pylon structure multi-objective optimization algorithm interactive algorithm multi-objective particle swarm optimization neural network Airplane Structure the mass maximum displacement original optimization design generations evolutions perform determine accurate simple efficient particle swarm optimization time consumption engineering practice large evaluation |
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