Progress in design optimization using evolutionary algorithms for aerodynamic problems

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Progress in design optimization using evolutionary algorithms for aerodynamic problems

Progress in design optimization using evolutionary algorithms for aerodynamic problems

Lian, Yongsheng / Oyama, Akira / Liou, Meng-Sing

AbstractEvolutionary algorithms (EAs) are useful tools in design optimization. Due to their simplicity, ease of use, and suitability for multi-objective design optimization problems, EAs have been applied to design optimization problems from various areas. In this paper we review the recent progress in design optimization using evolutionary algorithms to solve real-world aerodynamic problems. Examples are given in the design of turbo pump, compressor, and micro-air vehicles. The paper covers the following topics that are deemed important to solve a large optimization problem from a practical viewpoint: (1) hybridized approaches to speed up the convergence rate of EAs; (2) the use of surrogate model to reduce the computational cost stemmed from EAs; (3) reliability based design optimization using EAs; and (4) data mining of Pareto-optimal solutions.

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Title :

Progress in design optimization using evolutionary algorithms for aerodynamic problems

Contributors:

Lian, Yongsheng (author) / Oyama, Akira (author) / Liou, Meng-Sing (author)

Published in:

Progress in Aerospace Sciences ; 46 , 5-6 ; 199-223

Publication date :

2009-01-01

Size :

25 pages

ISSN :

DOI :

https://doi.org/10.1016/j.paerosci.2009.08.003

Type of media :

Article (Journal)

Type of material :

Electronic Resource

Language :

English

Keywords :

Multi-objective design optimization , Evolutionary algorithms , Surrogate model , Robust and reliability-based design , Data mining , NASA rotor 67 blade

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