Development of a multi-objective genetic algorithm for MDO problem

被引：0

作者：

Yao, Yifeng ^{[1
,2
]}

Yan, Pu ^{[1
,2
]}

Liu, Dayou ^{[1
,2
]}

机构：

[1] College of Computer Science and Technology, Jilin University

[2] Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University

来源：

Journal of Information and Computational Science | 2013年 / 10卷 / 06期

关键词：

Genetic local search; MDO; Multi-objective genetic algorithm;

D O I：

10.12733/jics20101661

中图分类号：

学科分类号：

摘要：

Engineering systems have become quite complicated in recent days. The requirements of design are complex and it is hard to meet them by considering only one discipline. In this paper, we suggest a hybrid Multi-objective Genetic Algorithm (MOGA) for a Multidisciplinary Design Optimization (MDO) model in engineering design. In order to get Pareto optimal solutions, we use local search to enhance the efficiency and effectiveness. We solve a problem of airplane wings optimization using MOGA. After compared with other MDO algorithms, we find the result shows that the proposed algorithm's performance has an advantage over previous work for these MDO problems. As the algorithm is evaluated based on practical data, we show that the approach can be used to solve MDO problems in the real world. Copyright © 2013 Binary Information Press.

引用

页码：1603 / 1612

页数：9

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