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2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications
A Modified Estimation of Distribution Algorithm for Numeric Optimization
Penang, Malaysia
September 27-September 29
ISBN: 978-0-7695-4514-1
ASCII Text
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Yuquan Li, Gexiang Zhang, Xiangxiang Zeng, Jixiang Cheng, Marian Gheorghe, Susan Elias, "A Modified Estimation of Distribution Algorithm for Numeric Optimization," Bio-Inspired Computing: Theories and Applications, International Conference on, pp. 114-119, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications, 2011.
 
 
BibTex
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@article{ 10.1109/BIC-TA.2011.14,
author = {Yuquan Li and Gexiang Zhang and Xiangxiang Zeng and Jixiang Cheng and Marian Gheorghe and Susan Elias},
title = {A Modified Estimation of Distribution Algorithm for Numeric Optimization},
journal ={Bio-Inspired Computing: Theories and Applications, International Conference on},
volume = {0},
year = {2011},
isbn = {978-0-7695-4514-1},
pages = {114-119},
doi = {http://doi.ieeecomputersociety.org/10.1109/BIC-TA.2011.14},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Bio-Inspired Computing: Theories and Applications, International Conference on
TI - A Modified Estimation of Distribution Algorithm for Numeric Optimization
SN - 978-0-7695-4514-1
SP114
EP119
A1 - Yuquan Li,
A1 - Gexiang Zhang,
A1 - Xiangxiang Zeng,
A1 - Jixiang Cheng,
A1 - Marian Gheorghe,
A1 - Susan Elias,
PY - 2011
KW - Modified EDA
KW - Centro-individual sampling
KW - Fuzzy c-means clustering
KW - Numeric optimization
VL - 0
JA - Bio-Inspired Computing: Theories and Applications, International Conference on
ER -
 
Estimation of distribution algorithms (EDAs) is a class of probabilistic model-building evolutionary algorithms, which is characterized by learning and sampling the probability distribution of the selected individuals. This paper proposes a modified estimation of distribution algorithm (mEDA) for numeric optimization. mEDA uses a novel sampling method, called centro-individual sampling, and a fuzzy c-means clustering technique to improve its performance. Extensive experiments conducted on a set of benchmark functions show that mEDA outperforms HPBILc, CEGDA, CEGNABGe and NichingEDA, reported in the literature, in terms of the quality of solutions.
Index Terms:
Modified EDA, Centro-individual sampling, Fuzzy c-means clustering, Numeric optimization
Citation:
Yuquan Li, Gexiang Zhang, Xiangxiang Zeng, Jixiang Cheng, Marian Gheorghe, Susan Elias, "A Modified Estimation of Distribution Algorithm for Numeric Optimization," bic-ta, pp.114-119, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications, 2011
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