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ASME Press Select Proceedings
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)Available to Purchase
Editor
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859896
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011
eBook Chapter
112 L1vy Flight Search Patterns in Genetic Algorithm Available to Purchase
By
Gang Huang
,
Gang Huang
State Key Laboratory of Digital Manufacturing Equipment & Technology,
Huazhong University of Science & Technology
, Wuhan, 430074
, China
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Yuanming Long
,
Yuanming Long
State Key Laboratory of Digital Manufacturing Equipment & Technology,
Huazhong University of Science & Technology
, Wuhan, 430074
, China
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Jinhang Li
,
Jinhang Li
State Key Laboratory of Digital Manufacturing Equipment & Technology,
Huazhong University of Science & Technology
, Wuhan, 430074
, China
; [email protected]
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Haiping Zhu
Haiping Zhu
State Key Laboratory of Digital Manufacturing Equipment & Technology,
Huazhong University of Science & Technology
, Wuhan, 430074
, China
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Page Count:
5
-
Published:2011
Citation
Huang, G, Long, Y, Li, J, & Zhu, H. "L1vy Flight Search Patterns in Genetic Algorithm." International Conference on Mechanical Engineering and Technology (ICMET-London 2011). Ed. Lee, G. ASME Press, 2011.
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In this paper, we constructed mathematical models for genetic algorithm (GA) and explored the searching process of genetic algorithm with statistical methods. Both two-dimensional and multidimensional benchmark functions were used to test the GA. Every group of the searching pace of GA performs power law distributions, even that the data is drawn from non-convergence cases. L1vy flight search patterns are proved to play an important role in the process. The efficiency of optimization process has something to do with the parameters of power law distributions. More interesting results and conclusions are given in the paper.
Abstract
Keywords
Introduction
Model Designing
Description of Genetic Algorithm
Two Dimensional Benchmark Functions
Multi-Dimensional Benchmark Function
Discussion and Conclusion
Acknowledgments
References
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