抄録
Use of genetic algorithms as an effective tool for searching sets of Pareto-optimal solutions in the context of multi-objective optimization problems has attracted considerable attention in various engineering fields. This paper presents a topology optimization method of framed structures using a genetic algorithm and the generalized transfer stiffness coefficient method (GTSCM). The GTSCM is well suited for the computation of constraint and the objective function values since stress and vibration analysis can easily be conducted by simply providing the structural data corresponding to the genotype of the individual. Two-objective optimization problems that minimize the total weight and maximize the first natural frequency under the displacement and the stress constraint are formulated, and a genetic algorithm based on the ground structure approach is developed. The present algorithm fully utilizes the benefits of the GTSCM in order to efficiently improve computation. Effective methods of genetic operations for the optimization of topology problems are also proposed.
| 元の言語 | 英語 |
|---|---|
| ページ（範囲） | 1137-1144 |
| ページ数 | 8 |
| ジャーナル | Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C |
| 巻 | 74 |
| 発行部数 | 5 |
| 出版物ステータス | 出版済み - 5 2008 |
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All Science Journal Classification (ASJC) codes
- Mechanical Engineering
これを引用
Topology optimization of a framed structure using generalized transfer stiffness coefficient method. / Bonkobara, Yasuhiro; Kondou, Takahiro; Sakao, Daisuke; Choi, Myung Soo; Kuroki, Hiroyuki; Sakamoto, Yuichiro.
：: Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 巻 74, 番号 5, 05.2008, p. 1137-1144.研究成果: ジャーナルへの寄稿 › 記事
}
TY - JOUR
T1 - Topology optimization of a framed structure using generalized transfer stiffness coefficient method
AU - Bonkobara, Yasuhiro
AU - Kondou, Takahiro
AU - Sakao, Daisuke
AU - Choi, Myung Soo
AU - Kuroki, Hiroyuki
AU - Sakamoto, Yuichiro
PY - 2008/5
Y1 - 2008/5
N2 - Use of genetic algorithms as an effective tool for searching sets of Pareto-optimal solutions in the context of multi-objective optimization problems has attracted considerable attention in various engineering fields. This paper presents a topology optimization method of framed structures using a genetic algorithm and the generalized transfer stiffness coefficient method (GTSCM). The GTSCM is well suited for the computation of constraint and the objective function values since stress and vibration analysis can easily be conducted by simply providing the structural data corresponding to the genotype of the individual. Two-objective optimization problems that minimize the total weight and maximize the first natural frequency under the displacement and the stress constraint are formulated, and a genetic algorithm based on the ground structure approach is developed. The present algorithm fully utilizes the benefits of the GTSCM in order to efficiently improve computation. Effective methods of genetic operations for the optimization of topology problems are also proposed.
AB - Use of genetic algorithms as an effective tool for searching sets of Pareto-optimal solutions in the context of multi-objective optimization problems has attracted considerable attention in various engineering fields. This paper presents a topology optimization method of framed structures using a genetic algorithm and the generalized transfer stiffness coefficient method (GTSCM). The GTSCM is well suited for the computation of constraint and the objective function values since stress and vibration analysis can easily be conducted by simply providing the structural data corresponding to the genotype of the individual. Two-objective optimization problems that minimize the total weight and maximize the first natural frequency under the displacement and the stress constraint are formulated, and a genetic algorithm based on the ground structure approach is developed. The present algorithm fully utilizes the benefits of the GTSCM in order to efficiently improve computation. Effective methods of genetic operations for the optimization of topology problems are also proposed.
UR - http://www.scopus.com/inward/record.url?scp=49149093903&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=49149093903&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:49149093903
VL - 74
SP - 1137
EP - 1144
JO - Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
JF - Nippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
SN - 0387-5024
IS - 5
ER -