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Erschienen in: Neural Computing and Applications 1/2018

02.07.2016 | Original Article

An improved differential evolution based on roulette wheel selection for shape and size optimization of truss structures with frequency constraints

verfasst von: V. Ho-Huu, T. Nguyen-Thoi, T. Truong-Khac, L. Le-Anh, T. Vo-Duy

Erschienen in: Neural Computing and Applications | Ausgabe 1/2018

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Abstract

Structural optimization with frequency constraints is well known as a highly nonlinear and complex optimization problem with many local optimum solutions. Therefore, to solve such problems effectively, designers need to use adequate optimization methods which can make a good balance between the computational cost and the quality of solutions. In this work, a novel differential evolution (DE) is proposed to solve the shape and size optimization problems for truss structures with frequency constraints. The proposed method, called ReDE, is a new version of the DE algorithm with two improvements. Firstly, the roulette wheel selection is employed to choose members for the mutation phase instead of random selection as in the conventional DE. Secondly, an elitist selection technique is applied to the selection phase instead of basic selection to improve the convergence speed of the method. The efficiency and reliability of the proposed method are demonstrated through five numerical examples. Numerical results reveal that the proposed algorithm outperforms many optimization methods in the literature.

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Metadaten
Titel
An improved differential evolution based on roulette wheel selection for shape and size optimization of truss structures with frequency constraints
verfasst von
V. Ho-Huu
T. Nguyen-Thoi
T. Truong-Khac
L. Le-Anh
T. Vo-Duy
Publikationsdatum
02.07.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 1/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2426-1

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