Automatic Grammar-Based Design of Heuristic Algorithms for Unconstrained Binary Quadratic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{deSouza:2018:evocop,
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author = "Marcelo {de Souza} and Marcus Ritt",
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title = "Automatic Grammar-Based Design of Heuristic Algorithms
for Unconstrained Binary Quadratic Programming",
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booktitle = "The 18th European Conference on Evolutionary
Computation in Combinatorial Optimisation, EvoCOP
2018",
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year = "2018",
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editor = "Arnaud Liefooghe and Manuel Lopez-Ibanez",
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series = "LNCS",
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volume = "10782",
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publisher = "Springer",
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pages = "67--84",
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address = "Parma, Italy",
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month = "4-6 " # apr,
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organisation = "Species",
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keywords = "genetic algorithms, genetic programming, Grammatical
evolution, Automatic algorithm configuration,
Metaheuristics",
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isbn13 = "978-3-319-77448-0",
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DOI = "doi:10.1007/978-3-319-77449-7_5",
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abstract = "Automatic methods have been applied to find good
heuristic algorithms to combinatorial optimization
problems. These methods aim at reducing human efforts
in the trial-and-error search for promising heuristic
strategies. We propose a grammar-based approach to the
automatic design of heuristics and apply it to binary
quadratic programming. The grammar represents the
search space of algorithms and parameter values. A
solution is represented as a sequence of categorical
choices, which encode the decisions taken in the
grammar to generate a complete algorithm.We use an
iterated F-race to evolve solutions and tune parameter
values. Experiments show that our approach can find
algorithms which perform better than or comparable to
state-of-the-art methods, and can even find new best
solutions for some instances of standard benchmark
sets.",
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notes = "EvoCOP2018 held in conjunction with EuroGP'2018
EvoMusArt2018 and EvoApplications2018
http://www.evostar.org/2018/cfp_evocop.php",
- }
Genetic Programming entries for
Marcelo de Souza
Marcus Ritt
Citations