Volume 7 Number 5 (May. 2012)
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JSW 2012 Vol.7(5): 1129-1135 ISSN: 1796-217X
doi: 10.4304/jsw.7.5.1129-1135

A Self-adaptive Optimization Removal Algorithm for Continuum Evolutionary Structural Topology

Yong Yang1, Wei-min Zhang1, 2, and Hong-lei Xie1
1College of Mechanical Engineering, Tongji University, Shanghai 201804, China
2Sino-German College, Tongji University, Shanghai 200092, China

Abstract—This paper presents a new self-adaptive optimization removal algorithm for evolutionary structural optimization (ESO) method. The elements rejection based on this algorithm is determined by their own attributes (statistical distribution of element sensitivity) rather than comparing the sensitivities to manual selective parameters in the traditional removal process. Thus, it avoids the choices and adjustments of a series of parameters, involves fewer subjective factors, and makes the removal process more adaptive. Furthermore, a self-adaptive coefficient is introduced to make the element removal vary with the iteration process and the calculation more stable. Besides, this algorithm is modified by the local secondary statistical distribution of sensitivity to depress the influence made by sensitivity concentration and improve the effectiveness of element removal. The numerous studies of structure cases based on this modified removal algorithm show that: the final results are reliable, and the optimization period is much shorter, the adaptability and robustness for different model are also well.

Index Terms—removal algorithm, adaptive optimization, evolutionary structural topology

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Cite: Yong Yang, Wei-min Zhang, and Hong-lei Xie, "A Self-adaptive Optimization Removal Algorithm for Continuum Evolutionary Structural Topology," Journal of Software vol. 7, no. 5, pp. 1129-1135, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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