Combinatorial Optimization by Gene Expression Programming: Inversion Revisited

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

@InProceedings{ferreira:2002:ASIA,

• author = "Candida Ferreira",
• title = "Combinatorial Optimization by Gene Expression Programming: Inversion Revisited",
• booktitle = "Proceedings of the Argentine Symposium on Artificial Intelligence",
• year = "2002",
• editor = "J. M. Santos and A. Zapico",
• pages = "160--174",
• address = "Santa Fe, Argentina",
• keywords = "genetic algorithms, genetic programming, GEP",
• URL = "http://www.gene-expression-programming.com/webpapers/ferreira-ASAI02.pdf",
• size = "9 pages",
• abstract = "Combinatorial optimisation problems require combinatorial-specific search operators so that populations of candidate solutions can evolve efficiently. Indeed, several researchers created modifications to the basic genetic operators of mutation and recombination in order to create high performing combinatorial-specific operators. However, it is not known which operators perform better as no systematic comparisons have been done. In this work, a new algorithm that explores a new chromosomal organisation based on multigene families is used. This new organization together with several combinatorial-specific search operators, namely, inversion, gene and sequence deletion/insertion, and restricted and generalised permutation, allow the algorithm to perform with high efficiency. The performance of the new algorithm is empirically compared on the 13- and 19-cities tour travelling salesperson problem, showing that the long abandoned inversion operator is by far the most efficient of the combinatorial operators. The efficiency and potentialities of the new algorithm are further demonstrated by solving a simple task assignment problem.",
• notes = "ASAI02 http://www.dc.uba.ar/people/profesores/santos/asai2002.html",

}

Genetic Programming entries for Candida Ferreira

Citations