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An Improved Strategy for Genetic Evolutionary Structural Optimization
Joint Authors
Cui, Nannan
Huang, Shiping
Ding, Xiaoyan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Genetic evolutionary structural optimization (GESO) method is an integration of the genetic algorithm (GA) and evolutionary structural optimization (ESO).
It has proven to be more powerful in searching for global optimal response and requires less computational efforts than ESO or GA.
However, GESO breaks down in the Zhou-Rozvany problem.
Furthermore, GESO occasionally misses the optimum layout of a structure in the evolution for its characteristic of probabilistic deletion.
This paper proposes an improved strategy that has been realized by MATLAB programming.
A penalty gene is introduced into the GESO strategy and the performance index (PI) is monitored during the optimization process.
Once the PI is less than the preset value which means that the calculation error of some element’s sensitivity is too big or some important elements are mistakenly removed, the penalty gene becomes active to recover those elements and reduce their selection probability in the next iterations.
It should be noted that this improvement strategy is different from “freezing,” and the recovered elements could still be removed, if necessary.
The improved GESO performs well in the Zhou-Rozvany problem.
In other numerical examples, the results indicate that the improved GESO has inherited the computational efficiency of GESO and more importantly increased the optimizing capacity and stability.
American Psychological Association (APA)
Cui, Nannan& Huang, Shiping& Ding, Xiaoyan. 2020. An Improved Strategy for Genetic Evolutionary Structural Optimization. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1122085
Modern Language Association (MLA)
Cui, Nannan…[et al.]. An Improved Strategy for Genetic Evolutionary Structural Optimization. Advances in Civil Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1122085
American Medical Association (AMA)
Cui, Nannan& Huang, Shiping& Ding, Xiaoyan. An Improved Strategy for Genetic Evolutionary Structural Optimization. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1122085
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1122085