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2009 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing
Evolutionary Algorithms for Optimization of Tobacco Leaf Groups Blending
Catholic University of Daegu, Daegu, Korea
May 27-May 29
ISBN: 978-0-7695-3642-2
ASCII Text
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Xia Peiyong, Ding Xiangqian, Yang Ning, "Evolutionary Algorithms for Optimization of Tobacco Leaf Groups Blending," 2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, pp. 144-148, 2009 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009.
 
 
BibTex
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@article{ 10.1109/SNPD.2009.91,
author = {Xia Peiyong and Ding Xiangqian and Yang Ning},
title = {Evolutionary Algorithms for Optimization of Tobacco Leaf Groups Blending},
journal ={2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing},
volume = {0},
year = {2009},
isbn = {978-0-7695-3642-2},
pages = {144-148},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2009.91},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - 2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
TI - Evolutionary Algorithms for Optimization of Tobacco Leaf Groups Blending
SN - 978-0-7695-3642-2
SP144
EP148
A1 - Xia Peiyong,
A1 - Ding Xiangqian,
A1 - Yang Ning,
PY - 2009
KW - Tobacco Leaf Groups Blending; Evolutionary Optimization;GA; PSO
VL - 0
JA - 2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
ER -
 
Traditional methods using for the design of tobacco leaf groups blending depend mostly on expert experiences. But they are lack control of the product quality and proved inefficient in practice. In this paper, we use the modified GA and PSO algorithms to help to optimize the leaf groups. The experimental results demonstrated that the modified GA and PSO algorithms are faster and more accurate when compared with the traditional methods; meanwhile PSO performs better than GA in General conditions.
Index Terms:
Tobacco Leaf Groups Blending; Evolutionary Optimization;GA; PSO
Citation:
Xia Peiyong, Ding Xiangqian, Yang Ning, "Evolutionary Algorithms for Optimization of Tobacco Leaf Groups Blending," snpd, pp.144-148, 2009 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009
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