Automatic Grammar-Based Design of Heuristic Algorithms for Unconstrained Binary Quadratic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{deSouza:2018:evocop,

• author = "Marcelo {de Souza} and Marcus Ritt",
• title = "Automatic Grammar-Based Design of Heuristic Algorithms for Unconstrained Binary Quadratic Programming",
• booktitle = "The 18th European Conference on Evolutionary Computation in Combinatorial Optimisation, EvoCOP 2018",
• year = "2018",
• editor = "Arnaud Liefooghe and Manuel Lopez-Ibanez",
• series = "LNCS",
• volume = "10782",
• publisher = "Springer",
• pages = "67--84",
• address = "Parma, Italy",
• month = "4-6 " # apr,
• organisation = "Species",
• keywords = "genetic algorithms, genetic programming, Grammatical evolution, Automatic algorithm configuration, Metaheuristics",
• isbn13 = "978-3-319-77448-0",
• DOI = "doi:10.1007/978-3-319-77449-7_5",
• 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.",
• 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