Novel ensemble collaboration method for dynamic scheduling problems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{durasevic:2022:GECCO,
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author = "Marko Durasevic and Lucija Planinic and
Francisco Javier {Gil Gala} and Domagoj Jakobovic",
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title = "Novel ensemble collaboration method for dynamic
scheduling problems",
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booktitle = "Proceedings of the 2022 Genetic and Evolutionary
Computation Conference",
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year = "2022",
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editor = "Alma Rahat and Jonathan Fieldsend and
Markus Wagner and Sara Tari and Nelishia Pillay and Irene Moser and
Aldeida Aleti and Ales Zamuda and Ahmed Kheiri and
Erik Hemberg and Christopher Cleghorn and Chao-li Sun and
Georgios Yannakakis and Nicolas Bredeche and
Gabriela Ochoa and Bilel Derbel and Gisele L. Pappa and
Sebastian Risi and Laetitia Jourdan and
Hiroyuki Sato and Petr Posik and Ofer Shir and Renato Tinos and
John Woodward and Malcolm Heywood and Elizabeth Wanner and
Leonardo Trujillo and Domagoj Jakobovic and
Risto Miikkulainen and Bing Xue and Aneta Neumann and
Richard Allmendinger and Inmaculada Medina-Bulo and
Slim Bechikh and Andrew M. Sutton and
Pietro Simone Oliveto",
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pages = "893--901",
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address = "Boston, USA",
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series = "GECCO '22",
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month = "9-13 " # jul,
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organisation = "SIGEVO",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, dispatching
rules, ensembles, unrelated machines, scheduling",
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isbn13 = "978-1-4503-9237-2",
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URL = "https://doi.org/10.1145/3512290.3528807",
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DOI = "doi:10.1145/3512290.3528807",
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abstract = "Dynamic scheduling problems are important optimisation
problems with many real-world applications. Since in
dynamic scheduling not all information is available at
the start, such problems are usually solved by
dispatching rules (DRs), which create the schedule as
the system executes. Recently, DRs have been
successfully developed using genetic programming.
However, a single DR may not efficiently solve
different problem instances. Therefore, much research
has focused on using DRs collaboratively by forming
ensembles. In this paper, a novel ensemble
collaboration method for dynamic scheduling is
proposed. In this method, DRs are applied independently
at each decision point to create a simulation of the
schedule for all currently released jobs. Based on
these simulations, it is determined which DR makes the
best decision and that decision is applied. The results
show that the ensembles easily outperform individual
DRs for different ensemble sizes. Moreover, the results
suggest that it is relatively easy to create good
ensembles from a set of independently evolved DRs.",
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notes = "GECCO-2022 A Recombination of the 31st International
Conference on Genetic Algorithms (ICGA) and the 27th
Annual Genetic Programming Conference (GP)",
- }
Genetic Programming entries for
Marko Durasevic
Lucija Planinic
Francisco Javier Gil Gala
Domagoj Jakobovic
Citations