DocumentCode
3229357
Title
Improved differential evolution algorithm used for load distribution of hot strip rolling
Author
Feng Yao ; Weidong Yang
Author_Institution
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
526
Lastpage
530
Abstract
To solve the problem that standard differential evolution algorithm is easy to premature convergence, here gives a new variant form-self-disturbance variation, and takes some improvement to it. New mutation could maintain the diversity of population, and the improvement could increase convergence speed. The improved method achieves performance improvement, and does not increase the time complexity of the original algorithm. Then, it is applied to the calculation of hot rolling load distribution.
Keywords
genetic algorithms; hot rolling; load distribution; evolutionary computation technique; hot strip rolling; improved differential evolution algorithm; load distribution; performance improvement; real-coded genetic algorithm; variant form-self-disturbance variation; Ice; differential evolutional algorithm; hot strip mills; load distribution; self-disturbance variation;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645180
Filename
5645180
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