A Comparative Study of Dispatching Rule Representations in Evolutionary Algorithms for the Dynamic Unrelated Machines Environment
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- @Article{9713874,
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author = "Lucija Planinic and Hrvoje Backovic and
Marko Durasevic and Domagoj Jakobovic",
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journal = "IEEE Access",
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title = "A Comparative Study of Dispatching Rule
Representations in Evolutionary Algorithms for the
Dynamic Unrelated Machines Environment",
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year = "2022",
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volume = "10",
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pages = "22886--22901",
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keywords = "genetic algorithms, genetic programming, Cartesian
genetic programming, Unrelated machines environment,
scheduling, solution representations, dispatching
rules",
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DOI = "doi:10.1109/ACCESS.2022.3151346",
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abstract = "Dispatching rules are most commonly used to solve
scheduling problems under dynamic conditions. Since
designing new dispatching rules is a time-consuming
process, it can be automated by using various machine
learning and evolutionary computation methods. In
previous research, genetic programming has been the
most commonly used method for automatically designing
new dispatching rules. However, there are many other
evolutionary methods that use representations other
than genetic programming that can be used to create
dispatching rules. Some, such as gene expression
programming, have already been used successfully, while
others, such as Cartesian genetic programming or
grammatical evolution, have not yet been used to
generate dispatching rules. In this paper, six
different methods (genetic programming, gene expression
programming, Cartesian genetic programming, grammatical
evolution, stack representation, and analytic
programming) for generating dispatching rules for the
unrelated machines environment are tested and the
results for various scheduling criteria are analysed.
It is also analysed how different individual sizes in
the tested methods affect the performance and average
size of the generated dispatching rules. The results
show that, with the exception of grammatical evolution
and analytic programming, all tested methods perform
quite similarly, with results depending on the selected
scheduling criterion. The results also show that
Cartesian genetic programming is the most resistant to
the occurrence of bloat and evolves dispatching rules
with the smallest average size.",
- }
Genetic Programming entries for
Lucija Planinic
Hrvoje Backovic
Marko Durasevic
Domagoj Jakobovic
Citations