飞机方案多目标优化的Pareto遗传算法

方卫国; 师瑞峰

飞机方案多目标优化的Pareto遗传算法

北京航空航天大学经济管理学院, 北京 100083

详细信息

作者简介:
方卫国(1969-),男,湖北云梦人,副教授, wgfang@buaa.edu.cn.

中图分类号: V 2216
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- 被引次数: 0
出版历程
- 收稿日期: 2002-06-13
- 网络出版日期: 2003-08-31

Pareto genetic algorithms for multi-objective optimization of aircraft conceptual design

School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要

摘要: 基于多目标优化问题Pareto最优解的概念,提出了一种求解非劣解集的多目标遗传算法,重点讨论了算法实现中非劣解集的筛选和适应度的计算.将该算法应用于假想的干线客机方案优化设计,要求巡航段升阻比和有用载荷系数两个目标最大,对优化结果进行了分析比较.研究结果显示出MOGA(Multi-Objective Genetic Algorithms)对飞机方案多目标优化设计具有良好的应用前景.
- 多目标规化 /
- 飞机设计 /
- 遗传算法 /
- Pareto最优
Abstract: Based on the Pareto optimal conception, a kind of MOGA(multi-objective genetic algorithms) seeking non-inferior solution set of MO problems was proposed, while the filtering of non-inferior solutions and the measure of fitness degree were discussed as an emphasis. The algorithm proposed was applied to a two-objective optimization of a hypothetical airliner conceptual design, where both the ratio of lift to drag in cruise segment and the useful load fraction were required to be maximized. The optimal solutions were analyzed and compared to the solution from uni-objective optimization using simple genetic algorithms. The research result demonstrates that MOGA possesses good application foreground for aircraft conceptual multi-objective optimization.
- multiple objective optimization /
- aircraft design /
- genetic algorithms /
- Pareto optimal

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参考文献(1)

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