Evolving priority rules for resource constrained project scheduling problem with genetic programming
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gp-bibliography.bib Revision:1.8098
- @Article{Dumic:2018:FGCS,
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author = "Mateja Dumic and Dominik Sisejkovic and
Rebeka Coric and Domagoj Jakobovic",
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title = "Evolving priority rules for resource constrained
project scheduling problem with genetic programming",
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journal = "Future Generation Computer Systems",
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year = "2018",
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volume = "86",
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pages = "211--221",
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keywords = "genetic algorithms, genetic programming, Resource
constrained scheduling, Hyper-heuristics",
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ISSN = "0167-739X",
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URL = "http://www.sciencedirect.com/science/article/pii/S0167739X1732441X",
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DOI = "doi:10.1016/j.future.2018.04.029",
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abstract = "The main task of scheduling is the allocation of
limited resources to activities over time periods to
optimize one or several criteria. The scheduling
algorithms are devised mainly by the experts in the
appropriate fields and evaluated over synthetic
benchmarks or real-life problem instances. Since many
variants of the same scheduling problem may appear in
practice, and there are many scheduling algorithms to
choose from, the task of designing or selecting an
appropriate scheduling algorithm is far from trivial.
Recently, hyper-heuristic approaches have been proven
useful in many scheduling domains, where machine
learning is applied to develop a customized scheduling
method. This paper is concerned with the resource
constrained project scheduling problem (RCPSP) and the
development of scheduling heuristics based on Genetic
programming (GP). The results show that this approach
is a viable option when there is a need for a
customized scheduling method in a dynamic environment,
allowing the automated development of a suitable
scheduling heuristic.",
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notes = "Also known as \cite{DUMIC2018211}",
- }
Genetic Programming entries for
Mateja Dumic
Dominik Sisejkovic
Rebeka Coric
Domagoj Jakobovic
Citations