On the Application of e-Lexicase Selection in the Generation of Dispatching Rules
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{Planinic:2021:CEC,
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author = "Lucija Planinic and Marko Durasevic and
Domagoj Jakobovic",
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booktitle = "2021 IEEE Congress on Evolutionary Computation (CEC)",
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title = "On the Application of e-Lexicase Selection in the
Generation of Dispatching Rules",
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year = "2021",
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editor = "Yew-Soon Ong",
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pages = "2125--2132",
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address = "Krakow, Poland",
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month = "28 " # jun # "-1 " # jul,
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keywords = "genetic algorithms, genetic programming, Training,
Sociology, Wheels, Dynamic scheduling, Dispatching,
Steady-state, lexicase, dispatching rules, scheduling",
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isbn13 = "978-1-7281-8393-0",
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DOI = "doi:10.1109/CEC45853.2021.9504982",
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abstract = "Dynamic online scheduling is a difficult problem which
commonly appears in the real world. This is because the
decisions have to be performed in a small amount of
time using only currently available incomplete
information. In such cases dispatching rules (DRs) are
the most commonly used methods. Since designing them
manually is a difficult task, this process has been
successfully automatised by using genetic programming
(GP). The quality of the evolved rules depends on the
problem instances that are used during the training
process. Previous studies demonstrated that careful
selection of problem instances on which the solutions
should be evaluated during evolution improves the
performance of the generated rules. This paper examines
the application of the epsilon-lexicase selection to
the design of DRs for the unrelated machines
scheduling. This selection offers a better solution
diversity since the individuals are selected based on a
smaller subset of instances, which leads to the
creation of DRs that perform well on the selected
instances. The experiments demonstrate that this type
of selection can significantly improve the results for
the Roulette Wheel and Elimination GP variants, while
achieving the same performance as the Steady State
Tournament GP. Furthermore, the epsilon-lexicase based
algorithms have a better convergence rate, which means
that the increased diversity in the population has a
positive effect on the evolution process.",
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notes = "Also known as \cite{9504982}",
- }
Genetic Programming entries for
Lucija Planinic
Marko Durasevic
Domagoj Jakobovic
Citations