Evolving dispatching rules for optimising many-objective criteria in the unrelated machines environment
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- @Article{Durasevic:GPEM,
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author = "Marko Durasevic and Domagoj Jakobovic",
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title = "Evolving dispatching rules for optimising
many-objective criteria in the unrelated machines
environment",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2018",
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volume = "19",
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number = "1-2",
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pages = "9--51",
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month = jun,
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note = "Special Issue on Automated Design and Adaptation of
Heuristics for Scheduling and Combinatorial
Optimisation",
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keywords = "genetic algorithms, genetic programming, Dispatching
rules, Many-objective optimisation, Scheduling,
Unrelated machines environment",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-017-9310-3",
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size = "43 pages",
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abstract = "Dispatching rules are often a method of choice for
solving various scheduling problems. Most often, they
are designed by human experts in order to optimise a
certain criterion. However, it is seldom the case that
a schedule should optimise a single criterion all
alone. More common is the case where several criteria
need to be optimised at the same time. This paper deals
with the problem of automatic design of dispatching
rules (DRs) by the use of genetic programming, for
many-objective scheduling problems. Four
multi-objective and many-objective algorithms,
including nondominated sorting genetic algorithm II,
nondominated sorting genetic algorithm III, harmonic
distance based multi-objective evolutionary algorithm
and multi-objective evolutionary algorithm based on
decomposition, have been used in order to obtain sets
of Pareto optimal solutions for various many-objective
scheduling problems. Through experiments it was shown
that automatically generated multi-objective DRs not
only achieve good performance when compared to standard
DRs, but can also outperform automatically generated
single objective DRs for most criteria combinations.",
- }
Genetic Programming entries for
Marko Durasevic
Domagoj Jakobovic
Citations