Evolving similarity coefficients for the solution of cellular manufacturing problems

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

  author =       "Christos Dimopoulos and Neil Mort",
  title =        "Evolving similarity coefficients for the solution of
                 cellular manufacturing problems",
  booktitle =    "Proceedings of the Congress on Evolutionary
                 Computation (CEC 2000)",
  year =         "2000",
  pages =        "617--624",
  volume =       "1",
  address =      "La Jolla Marriott Hotel La Jolla, California, USA",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "6-9 " # jul,
  organisation = "IEEE Neural Network Council (NNC), Evolutionary
                 Programming Society (EPS), Institution of Electrical
                 Engineers (IEE)",
  publisher =    "IEEE Press",
  email =        "chris_dimop@hotmail.com",
  keywords =     "genetic algorithms, genetic programming, cell
                 formation, similarity coefficients, engineering
                 applications, Jaccard similarity coefficient, cell
                 formation problem, cellular manufacturing problems,
                 cellular manufacturing system, clustering procedure,
                 evolved coefficients, evolving similarity coefficients,
                 genetic programming algorithm, hierarchical clustering
                 procedures, manufacturing optimisation problem,
                 similarity coefficients, simple cell formation
                 problems, flexible manufacturing systems, pattern
  DOI =          "doi:10.1109/CEC.2000.870355",
  ISBN =         "0-7803-6375-2",
  abstract =     "The cell formation problem is a classic manufacturing
                 optimisation problem associated with the implementation
                 of a cellular manufacturing system. A variety of
                 hierarchical clustering procedures have been proposed
                 for the solution of this problem. Essential for the
                 operation of a clustering procedure is the
                 determination of a form of similarity between the
                 objects that are going to be grouped. In this paper we
                 employ a Genetic Programming algorithm for the
                 evolution of new similarity coefficients for the
                 solution of simple cell formation problems. Evolved
                 coefficients are tested against the well-known
                 Jaccard's similarity coefficient on a large number of
                 problems taken from the literature",
  notes =        "also called \cite{dimopoulos:2000:ESCSCMP}
                 \cite{870355}. CEC-2000 - A joint meeting of the IEEE,
                 Evolutionary Programming Society, Galesia, and the

                 IEEE Catalog Number = 00TH8512,

                 Library of Congress Number = 00-018644",

Genetic Programming entries for Christos Dimopoulos Neil Mort