On the application of Genetic Programming to the envelope reduction problem

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Koohestani:2012:CEEC,
  author =       "Behrooz Koohestani and Riccardo Poli",
  title =        "On the application of Genetic Programming to the
                 envelope reduction problem",
  booktitle =    "4th Computer Science and Electronic Engineering
                 Conference",
  year =         "2012",
  editor =       "Maria Fasli",
  pages =        "53--58",
  address =      "University of Essex, UK",
  month =        "12-13 " # sep,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, sparse
                 matrix",
  DOI =          "doi:10.1109/CEEC.2012.6375378",
  size =         "6 pages",
  abstract =     "Large sparse matrices characterise the linear systems
                 found in various scientific and engineering domains
                 such as fluid mechanics, structural engineering, finite
                 element analysis and network analysis. The ordering of
                 the rows and columns of a matrix determines how close
                 to the main diagonal its non-zero elements are, which
                 in turn greatly influences the performance of solvers
                 for the associated linear system. The reduction of the
                 sum of the distance of non-zero elements from the
                 matrix's main diagonal, a quantity known as envelope,
                 is thus a key issue in many domains. Formally, the
                 problem consists in finding a permutation of the rows
                 and columns of a matrix which minimises its envelope.
                 The problem is known to be NP-complete. A considerable
                 number of methods have been proposed for reducing the
                 envelope. These methods are mostly based on
                 graph-theoretic concepts. While metaheuristic
                 approaches are viable alternatives to classical
                 optimisation techniques in a variety of domains, in the
                 case of the envelope reduction problem, there has been
                 a very limited exploration of such methods. In this
                 paper, a Genetic Programming system capable of reducing
                 the envelope of sparse matrices is presented. We
                 evaluate our method on a set of standard benchmarks
                 from the Harwell-Boeing sparse matrix collection
                 against four state-of-the-art algorithms from the
                 literature. The results obtained show that the proposed
                 method compares very favourably with these
                 algorithms.",
  notes =        "tree GP, ERP, permutation, math, matlab.

                 CEEC 2012 http://www.essex.ac.uk/csee/research/ceec/",
}

Genetic Programming entries for Behrooz Koohestani Riccardo Poli

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