Evolving and Reusing Bin Packing Heuristic through Grammatical Differential Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.8178

@InProceedings{Sotelo-Figueroa:2013:nabic,

• author = "Marco A. Sotelo-Figueroa and Hector Jose {Puga Soberanes} and Juan {Martin Carpio} and Hector J. {Fraire Huacuja} and Laura {Cruz Reyes} and Jorge A. Soria-Alcaraz",
• title = "Evolving and Reusing Bin Packing Heuristic through Grammatical Differential Evolution",
• booktitle = "5th World Congress on Nature and Biologically Inspired Computing",
• year = "2013",
• editor = "Simone Ludwig and Patricia Melin and Ajith Abraham and Ana Maria Madureira and Kendall Nygard and Oscar Castillo and Azah Kamilah Muda and Kun Ma and Emilio Corchado",
• pages = "92--98",
• address = "Fargo, USA",
• month = "12-14 " # aug,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, Grammatical Evolution, Bin Packing, Grammatical Differential Evolution, Heuristics, Differential Evolution, Best-Fit",
• isbn13 = "978-1-4799-1415-9",
• URL = "http://www.mirlabs.net/nabic13/proceedings/html/paper24.xml",
• DOI = "doi:10.1109/NaBIC.2013.6617844",
• size = "7 pages",
• abstract = "The Bin Packing Problem is a classic optimisation problem, over the years many heuristics have been developed to obtain better results. There are many approaches to generating heuristics automatically, those approaches are based Genetic Programming, but the heuristics generated sometimes can not be applied to the problem. Recently in the Artificial Intelligence field, the Grammar Evolution approach emerged, which generated expressions like the generated by Genetic Programming; these algorithms evolve into a grammar based on the Backus Naur Form. In the present work we show a Grammar Evolution based on Differential Evolution, which automatically generated heuristics for the Bin Packing Problem instances. Those heuristics generated by the Grammar Evolution are like the Best-Fit heuristic which was designed by humans. The work's goal is to prove that is feasible to use the Grammar Evolution to automatically generate and reusing heuristics which have at least the same performance than the best generated by humans, we also propose a Grammar to improve the results obtained for a Grammar based on Genetic Programming.",
• notes = "USB, IEEE Catalog Number: CFP1395H-POD",
• notes = "Also known as \cite{6617844}",

}

Genetic Programming entries for Marco Aurelio Sotelo Figueroa Hector J Puga Juan Martin Carpio-Valadez Hector Joaquin Fraire Huacuja Laura Cruz Jorge Alberto Soria-Alcaraz

Citations