Evolutionary Lossless Compression with GP-ZIP

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Ahmad Kattan and Riccardo Poli",
  title =        "Evolutionary Lossless Compression with {GP-ZIP}",
  booktitle =    "2008 IEEE World Congress on Computational
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "2468--2472",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0569.pdf",
  DOI =          "doi:10.1109/CEC.2008.4631128",
  abstract =     "In this paper we propose a new approach for applying
                 Genetic Programming to loss-less data compression based
                 on combining well-known lossless compression
                 algorithms. The file to be compressed is divided into
                 chunks of a predefined length, and GP is asked to find
                 the best possible compression algorithm for each chunk
                 in such a way to minimise the total length of the
                 compressed file. This technique is referred to as
                 ''GP-zip''. The compression algorithms available to
                 GP-zip (its function set) are: Arithmetic coding (AC),
                 Lempel-Ziv-Welch (LZW), Unbounded Prediction by Partial
                 Matching (PPMD), Run Length Encoding (RLE), and Boolean
                 Minimisation. In addition, two transformation
                 techniques are available: Burrows-Wheeler
                 Transformation (BWT) and Move to Front (MTF). In
                 experimentation with this technique, we show that when
                 the file to be compressed is composed of heterogeneous
                 data fragments (as is the case, for example, in archive
                 files), GP-zip is capable of achieving compression
                 ratios that are superior to those obtained with
                 well-known compression algorithms.",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",

Genetic Programming entries for Ahmed Kattan Riccardo Poli