Job-Shop Scheduling with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7410
- @InProceedings{Miyashita:2000:GECCO,
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author = "Kazuo Miyashita",
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title = "Job-Shop Scheduling with Genetic Programming",
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pages = "505--512",
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year = "2000",
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publisher = "Morgan Kaufmann",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2000)",
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editor = "Darrell Whitley and David Goldberg and
Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
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address = "Las Vegas, Nevada, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "10-12 " # jul,
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-55860-708-0",
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URL = "
http://gpbib.cs.ucl.ac.uk/gecco2000/GP041.pdf",
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DOI = "
doi:10.5555/2933718.2933809",
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size = "8 pages",
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abstract = "In order to solve a real-time scheduling problem, a
computationally intensive search-based optimization
method is not practical, but the efficient dispatching
rule that is well-customized for the specific problem
at hand can be an effective problem solving method. A
dispatching rule is scheduling heuristics that decide
the sequence of operations to be executed at each
resource in the scheduling problem. However, developing
a customized dispatching rule for specific scheduling
problems is an arduous task even for domain experts or
researchers in the scheduling problem. In this
research, the author views scheduling problems as
multi-agent problem solving and proposes an approach
for synthesizing the dispatching rule by means of
Genetic Programming (GP). In the preliminary
experiments, the author got the results showing that
GP-based multi-agent dispatching scheduler outperformed
the well-known dispatching rules.",
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notes = "A joint meeting of the ninth International Conference
on Genetic Algorithms (ICGA-2000) and the fifth Annual
Genetic Programming Conference (GP-2000) Part of
\cite{whitley:2000:GECCO}",
- }
Genetic Programming entries for
Kazuo Miyashita
Citations