東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Genetic search methods for multicrit...

Lin, Chyi-Yeu.

FindBook

Google Book

Amazon

博客來

Genetic search methods for multicriterion optimal design of viscoelastically damped structures.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Genetic search methods for multicriterion optimal design of viscoelastically damped structures./
作者:	Lin, Chyi-Yeu.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 1991,
面頁冊數:	220 p.
附註:	Source: Dissertations Abstracts International, Volume: 53-12, Section: B.
Contained By:	Dissertations Abstracts International53-12B.
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9219207

Genetic search methods for multicriterion optimal design of viscoelastically damped structures.
Lin, Chyi-Yeu.

Genetic search methods for multicriterion optimal design of viscoelastically damped structures. - Ann Arbor : ProQuest Dissertations & Theses, 1991 - 220 p.

Source: Dissertations Abstracts International, Volume: 53-12, Section: B.

Thesis (Ph.D.)--University of Florida, 1991.

This item must not be sold to any third party vendors.

This study examines the use of genetic search techniques in the multicriterion optimal design of structural systems. The global nature of these search techniques makes them better suited for design spaces that are known to be disjoint or nonconvex. The study was motivated by an application involving the optimal design of viscoelastically damped composite structures. In addition to the multicriterion nature of this design problem, its design space is a mix of continuous, integer, and discrete design variables. The more traditional mathematical programming based methods of optimization are known to generate suboptimal designs for this class of problems. Genetic algorithms belong to a general category of stochastic search methods. An optimal design is located by combining favorable characteristics of several designs in such a way as to maximize a defined fitness function. The transformation operators that facilitate this combination have their philosophical basis in biological principles of evolution. As shown in this work, the method can easily accommodate the presence of integer and discrete variables in the design space. An extension of genetic search to the multicriterion optimal design problem is presented in this work. This design problem requires that an optimal design be generated for which each of the criteria are simultaneously optimized. Two distinct strategies for generating such designs are presented in this work. A distinct feature of these strategies is that they allow for a simultaneous generation of optimal designs in problems where the individual criterion are weighted differently. The design of viscoelastically damped composite beam structures considered in this work was based on a three-dimensional finite element solution. This analysis is computationally demanding, and in order for it to be used for optimization, approximations to the exact analysis were required. A multilayer perceptron model of an artificial neural network was used to map the input-output relationships between the design variables and the output response, and this approximation was used in the optimal design in lieu of the exact analysis. Optimal designs of composite beams for minimum weight and maximum damping were obtained using this approach.Subjects--Topical Terms:

586835
Engineering.

Genetic search methods for multicriterion optimal design of viscoelastically damped structures.
LDR:03363nmm a2200313 4500 001 2206904
005 20190906083324.5
008 201008s1991 ||||||||||||||||| ||eng d
035 $a (MiAaPQ)AAI9219207
035 $a AAI9219207
040 $a MiAaPQ $c MiAaPQ
100 1 $a Lin, Chyi-Yeu. $3 3433828
245 1 0 $a Genetic search methods for multicriterion optimal design of viscoelastically damped structures.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 1991
300 $a 220 p.
500 $a Source: Dissertations Abstracts International, Volume: 53-12, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Hajela, Prabhat.
502 $a Thesis (Ph.D.)--University of Florida, 1991.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a This study examines the use of genetic search techniques in the multicriterion optimal design of structural systems. The global nature of these search techniques makes them better suited for design spaces that are known to be disjoint or nonconvex. The study was motivated by an application involving the optimal design of viscoelastically damped composite structures. In addition to the multicriterion nature of this design problem, its design space is a mix of continuous, integer, and discrete design variables. The more traditional mathematical programming based methods of optimization are known to generate suboptimal designs for this class of problems. Genetic algorithms belong to a general category of stochastic search methods. An optimal design is located by combining favorable characteristics of several designs in such a way as to maximize a defined fitness function. The transformation operators that facilitate this combination have their philosophical basis in biological principles of evolution. As shown in this work, the method can easily accommodate the presence of integer and discrete variables in the design space. An extension of genetic search to the multicriterion optimal design problem is presented in this work. This design problem requires that an optimal design be generated for which each of the criteria are simultaneously optimized. Two distinct strategies for generating such designs are presented in this work. A distinct feature of these strategies is that they allow for a simultaneous generation of optimal designs in problems where the individual criterion are weighted differently. The design of viscoelastically damped composite beam structures considered in this work was based on a three-dimensional finite element solution. This analysis is computationally demanding, and in order for it to be used for optimization, approximations to the exact analysis were required. A multilayer perceptron model of an artificial neural network was used to map the input-output relationships between the design variables and the output response, and this approximation was used in the optimal design in lieu of the exact analysis. Optimal designs of composite beams for minimum weight and maximum damping were obtained using this approach.
590 $a School code: 0070.
650 4 $a Engineering. $3 586835
650 4 $a Mechanics. $3 525881
690 $a 0537
690 $a 0346
710 2 $a University of Florida. $3 718949
773 0 $t Dissertations Abstracts International $g 53-12B.
790 $a 0070
791 $a Ph.D.
792 $a 1991
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9219207