An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Huang:2022:EuroGP,
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author = "Zhixing Huang and Fangfang Zhang and Yi Mei and
Mengjie Zhang",
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title = "An Investigation of Multitask Linear Genetic
Programming for Dynamic Job Shop Scheduling",
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booktitle = "EuroGP 2022: Proceedings of the 25th European
Conference on Genetic Programming",
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year = "2022",
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editor = "Eric Medvet and Gisele Pappa and Bing Xue",
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series = "LNCS",
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volume = "13223",
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publisher = "Springer Verlag",
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address = "Madrid, Spain",
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pages = "162--178",
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month = "20-22 " # apr,
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organisation = "EvoStar, Species",
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note = "Best paper",
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keywords = "genetic algorithms, genetic programming, Linear
genetic programming, Multitask, Hyper-heuristic,
Dynamic job shop scheduling",
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isbn13 = "978-3-031-02055-1",
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DOI = "doi:10.1007/978-3-031-02056-8_11",
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abstract = "Dynamic job shop scheduling has a wide range of
applications in reality such as order picking in
warehouse. Using genetic programming to design
scheduling heuristics for dynamic job shop scheduling
problems becomes increasingly common. In recent years,
multitask genetic programming-based hyper-heuristic
methods have been developed to solve similar dynamic
scheduling problem scenarios simultaneously. However,
all of the existing studies focus on the tree-based
genetic programming. In this paper, we investigate the
use of linear genetic programming, which has some
advantages over tree-based genetic programming in
designing multitask methods, such as building block
reusing. Specifically, this paper makes a preliminary
investigation on several issues of multitask linear
genetic programming. The experiments show that the
linear genetic programming within multitask frameworks
have a significantly better performance than solving
tasks separately, by sharing useful building blocks.",
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notes = "http://www.evostar.org/2022/eurogp/ Part of
\cite{Medvet:2022:GP} EuroGP'2022 held inconjunction
with EvoApplications2022 EvoCOP2022 EvoMusArt2022",
- }
Genetic Programming entries for
Zhixing Huang
Fangfang Zhang
Yi Mei
Mengjie Zhang
Citations