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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
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SP - 965
EP - 975
%@ 1869-1951
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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.
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