Multi-objective optimization for aerodynamic designs by using ARMOGAs

被引：5

作者：

Obayashi, S ^{[1
]}

Sasaki, D ^{[1
]}

机构：

[1] Tohoku Univ, Inst Fluid Sci, Sendai, Miyagi 980, Japan

来源：

SEVENTH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND GRID IN ASIA PACIFIC REGION, PROCEEDINGS | 2004年

关键词：

D O I：

10.1109/HPCASIA.2004.1324064

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Global trade-offs for aerodynamic design of Supersonic Transport (SST) have been investigated by Multi-Objective Evolutionary Algorithms (MOEAs). The objectives are to reduce both drag and sonic boom to make next-generation SST more feasible. Adaptive Range Multi-Objective Genetic Algorithms (ARMOGAs) are utilized for the efficient search. The trade-offs are analysed by Self-Organizing Map (SOM), which provides a topology preserving mapping from the high dimensional space to two dimensions. ARMOGAs and SOM can be good design tools to conduct aerodynamic design optimizations and analyse the results.

引用

页码：396 / 403

页数：8

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