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CLC number: TP393.11
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2011-11-04
Cited: 3
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A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints
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Lei Zhang, Mattias Lampe, Zhi Wang. A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints[J]. Journal of Zhejiang University Science C, 2011, 12(12): 965-975.
@article{title="A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints",
author="Lei Zhang, Mattias Lampe, Zhi Wang",
journal="Journal of Zhejiang University Science C",
volume="12",
number="12",
pages="965-975",
year="2011",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1100045"
}
%0 Journal Article
%T A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints
%A Lei Zhang
%A Mattias Lampe
%A Zhi Wang
%J Journal of Zhejiang University SCIENCE C
%V 12
%N 12
%P 965-975
%@ 1869-1951
%D 2011
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1100045
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T1 - A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints
A1 - Lei Zhang
A1 - Mattias Lampe
A1 - Zhi Wang
J0 - Journal of Zhejiang University Science C
VL - 12
IS - 12
SP - 965
EP - 975
%@ 1869-1951
Y1 - 2011
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1100045
Abstract: With the advance of automation technology, the scale of industrial communication networks at field level is growing. Guaranteeing real-time performance of these networks is therefore becoming an increasingly difficult task. This paper addresses the optimization of device allocation in industrial Ethernet networks with real-time constraints (DAIEN-RC). Considering the inherent diversity of real-time requirements of typical industrial applications, a novel optimization criterion based on relative delay is proposed. A hybrid genetic algorithm incorporating a reduced variable neighborhood search (GA-rVNS) is developed for DAIEN-RC. Experimental results show that the proposed novel scheme achieves a superior performance compared to existing schemes, especially for large scale industrial networks.
[1]Bean, J.C., 1994. Genetic algorithms and random keys for sequencing and optimization. INFORMS J. Comput., 6(2):154-160.
[2]Carro-Calvo, L., Salcedo-Sanz, S., Portilla-Figueras, J.A., Ortiz-Garcia, E.G., 2010. A genetic algorithm with switch-device encoding for optimal partition of switched industrial Ethernet networks. J. Network Comput. Appl., 33(4):375-382.
[3]Elbaum, R., Sidi, M., 1996. Topological design of local-area networks using genetic algorithms. IEEE/ACM Trans. Network., 4(5):766-778.
[4]Felser, M., 2005. Real-time Ethernet-industry prospective. Proc. IEEE, 93(6):1118-1129.
[5]Gen, M., Cheng, R., 1997. Genetic Algorithm and Engineering Optimization. Wiley, New York.
[6]Gen, M., Cheng, R.W., Lin, L., 2008. Network Model and Optimization Multiobjective Genetic Algorithm Approach. Springer Verlag Berlin Heidelberg, p.274-283.
[7]Georges, G.P., Krommenacker, N., Divoux, T., Rondeau, E., 2006. A design process of switched Ethernet architectures according to real-time application constraints. Eng. Appl. Artif. Intell., 19(3):335-344.
[8]Hansen, P., Mladenovic, N., 2001. Variable neighborhood search: principles and applications. Eur. J. Oper. Res., 130(3):449-467.
[9]Hart, W.E., Rosin, C.R., Belew, R.K., Morris, G.M., 2000. Improved Evolutionary Hybrids for Flexible Ligand Docking in AutoDock. In: Floudas, C.A., Pardalos, P.M. (Eds.), Optimization of Computational Chemistry and Molecular Biology. Kluwer, the Netherlands, p.209-230.
[10]IEC 61784-2, 2005. Digital Data Communications for Measurement and Control - Part 2: Additional Profiles for ISO/IEC 8802-3 Based Communication Networks in Real-Time Applications. IEC, Switzerland.
[11]IEEE 802.1Q, 2003. Virtual Bridged Local Area Networks. IEEE, New York, USA.
[12]Jasperneite, J., Neumann, P., Theis, M., Watson, K., 2002. Deterministic Real-Time Communication with Switched Ethernet. Proc. 4th IEEE Int. Workshop on Factory Communication Systems, p.11-18.
[13]Kjellsson, J., Vallestad, A.E., Steigmann, R., Dzung, D., 2009. Integration of a wireless I/O interface for Profibus and Profinet for factory automation. IEEE Trans. Ind. Electron., 56(10):4279-4287.
[14]Krommenacker, N., Divoux, T., Rondeau, E., 2002. Using Genetic Algorithm to Design Switched Ethernet Industrial Network. Proc. IEEE Int. Symp. on Industrial Electronics, 1:152-157.
[15]Li, F., Zhang, Q., Zhang, W., 2007. Graph partitioning strategy for the topology design of industrial network. IET Commun., 1(6):1104-1110.
[16]Michalewicz, Z., 1994. Genetic Algorithms+Data Structures= Evolution Programs. Springer Verlag, New York.
[17]Mladenovic, N., Hansen, P., 1997. Variable neighborhood search. Comput. Oper. Res., 24(11):1097-1100.
[18]Song, Y., Koubaa, A., Simonot, F., 2002. Switched Ethernet for Real-Time Industrial Communication Modelling and Message Buffering Delay Evaluation. Proc. 4th Int. Workshop on Factory Communication Systems, p.27-30.
[19]Tang, M.L., Yao, X., 2007. A memetic algorithm for VLSI floorplanning. IEEE Trans. Syst. Man Cybern. B, 37(1):62-69.
[20]Wang, Z., Song, Y.Q., Chen, J.M., Sun, Y.X., 2002. Real-time Characteristics of Ethernet and Its Improvement. Proc. 4th World Congress on Intelligent Control and Automation, 2:1311-1318.
[21]Zhang, L., Wang, Z., 2010. Real-Time Performance Evaluation in Hybrid Industrial Ethernet Networks. Proc. 8th World Congress on Intelligent Control and Automation, p.1842-1845.
[22]Zhang, Q., Zhang, W.D., 2007. Using genetic algorithm to design switched Ethernet industrial network. Eng. Appl. Artif. Intell., 20(1):79-88.
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