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Abstract
The machine-part cell formation is a NP- complete combinational optimization in cellular manufacturing system. Previous researches have revealed that although the genetic algorithm (GA) can get high quality solutions, special selection strategy, crossover and mutation operators as well as the parameters must be defined previously to solve the problem efficiently and flexibly. The Estimation of Distribution Algorithms (EDAs) has recently been recognized as a new computing paradigm in evolutionary computation which can overcome some drawbacks of the traditional GA mentioned above. In this paper, two kinds of the EDAs, UMDA and EBNABIC are applied to solve the machine-part cell formation problem. Simulation results on six well known problems show that the UMDA and EBNABIC can attain satisfied solutions more simply and efficiently.
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Authors and Affiliations
Shijiazhuang Institute of Railway Technology, Shijiazhuang, 050041, China
Qingbin Zhang, Lihong Bi & Boyuan Ma
Hebei Academy of Sciences, Shijiazhuang, 050081, China
Bo Liu
Information Center of Hebei Education Department, Shijiazhuang, 050000, China
Zhuangwei Wang
- Qingbin Zhang
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- Bo Liu
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- Lihong Bi
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- Zhuangwei Wang
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- Boyuan Ma
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Editors and Affiliations
Faculty of Computer Science, China University of Geosciences, 430074, Wuhan, Hubei, P.R. China
Zhihua Cai
School of Computer Science, China University of Geosciences, 430074, Wuhan, Hubei, China
Zhenhua Li
Computation Center, Wuhan University, 430072, Wuhan, Hubei, China
Zhuo Kang
School of Computer Science and Engineering, The University of Aizu, 965-8580, i, Aizu-Wakamatsu City, Fukushima, Japan
Yong Liu
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Zhang, Q., Liu, B., Bi, L., Wang, Z., Ma, B. (2009). Estimation of Distribution Algorithms for the Machine-Part Cell Formation. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2009. Lecture Notes in Computer Science, vol 5821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04843-2_10
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