Genetic Programming for Lifetime Maximization in Wireless Sensor Networks with a Mobile Sink
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Li:2017:SEAL,
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author = "Ying Li and Zhixing Huang and Jinghui Zhong and
Liang Feng",
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title = "Genetic Programming for Lifetime Maximization in
Wireless Sensor Networks with a Mobile Sink",
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booktitle = "Proceedings of the 11th International Conference on
Simulated Evolution and Learning, SEAL-2017",
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year = "2017",
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editor = "Yuhui Shi and Kay Chen Tan and Mengjie Zhang and
Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and
Martin Middendorf and Yaochu Jin",
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volume = "10593",
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series = "Lecture Notes in Computer Science",
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pages = "774--785",
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address = "Shenzhen, China",
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month = nov # " 10-13",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-68759-9",
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URL = "https://doi.org/10.1007/978-3-319-68759-9_63",
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DOI = "doi:10.1007/978-3-319-68759-9_63",
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abstract = "Maximizing the lifetime of Wireless Sensor Network
(WSN) with a mobile sink is a challenging and important
problem that has attracted increasing research
attentions. In the literature, heuristic based
approaches have been proposed to solve the problem,
such as the Greedy Maximum Residual Energy (GMRE) based
method. However, existing heuristic based approaches
highly rely on expert knowledge, which makes them
inconvenient for practical applications. Taking this
cue, in this paper, we propose an automatic method to
construct heuristic for sink routing based on Genetic
Programming (GP) approach. Empirical study shows that
the proposed method can generate promising heuristics
that achieve superior performance against existing
methods with respect to the global lifetime of WSN.",
- }
Genetic Programming entries for
Ying Li
Zhixing Huang
Jinghui Zhong
Liang Feng
Citations