Combined Use Of Genetic Programming And Decomposition Techniques For The Induction Of Generalized Approximate Throughput Formulas In Short Exponential Production Lines With Buffers

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

@InProceedings{oai:CiteSeerPSU:560410,
  title =        "Combined Use Of Genetic Programming And Decomposition
                 Techniques For The Induction Of Generalized Approximate
                 Throughput Formulas In Short Exponential Production
                 Lines With Buffers",
  author =       "Chrissoleon Papadopoulos and Athanasios Tsakonas and 
                 George Dounias",
  year =         "2002",
  booktitle =    "Proceedings of the 30th International Conference on
                 Computers \& Industrial Engineering",
  editor =       "Chrissoleon Papadopoulos and 
                 Evangelos Triantaphyllou",
  address =      "Tinos Island, Greece",
  month =        "28 " # jun # "-2 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  citeseer-isreferencedby = "oai:CiteSeerPSU:94604",
  citeseer-references = "oai:CiteSeerPSU:20226",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:560410",
  rights =       "unrestricted",
  URL =          "http://decision.fme.aegean.gr/members/tsakonas/ICCIE-2002-040401.pdf",
  URL =          "http://citeseer.ist.psu.edu/560410.html",
  size =         "6 pages",
  abstract =     "An attempt is made to combine standard decomposition
                 techniques and genetic programming approaches, for the
                 induction of generalized approximate throughput
                 formulas in short exponential serial production lines
                 with finite intermediate buffers. The domain of serial
                 production lines lacks the existence of general
                 formulas for acquiring useful measurements and line
                 characteristics, such as throughput. Throughput
                 approximation in literature takes place usually with
                 the aid of algorithmic computer-based decomposition
                 techniques. In this paper, decomposition-based data for
                 every different number of stations are used as training
                 cases into a genetic programming scheme, which tries to
                 generalize the calculation of throughput within a
                 single mathematical formula. The proposed formula,
                 obtains accuracy higher than 99% for the training
                 (i.e,. known) data, whereas, it deviates, on average,
                 5-15% from the accurate decomposed value, for testing
                 (i.e. unknown) production line characteristics.",
  notes =        "Two volumes, 1,058 pages long (total)
                 http://www.imse.lsu.edu/vangelis/index.html?http://cda4.imse.lsu.edu/books1/Tinos2002CompsAndIEConference/Tinos2002Proceedings.htm",
}

Genetic Programming entries for Chrissoleon T Papadopoulos Athanasios D Tsakonas Georgios Dounias

Citations