Genetic algorithms : a useful optimization method for manufacturing problems

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@Article{Ficko:2004:AJME,
  author =       "Mirko Ficko and Miha Kovacic and Miran Brezocnik",
  title =        "Genetic algorithms : a useful optimization method for
                 manufacturing problems",
  journal =      "Academic Journal of Manufacturing Engineering",
  year =         "2004",
  volume =       "2",
  number =       "1",
  pages =        "21--26",
  keywords =     "genetic algorithms, genetic programming, optimisation,
                 facility layout, flexible manufacturing systems",
  ISSN =         "1583-7904",
  abstract =     "a very useful method for solving g the manufacturing
                 problems, and optimising the manufacturing process,
                 i.e. the genetic algorithms (GAs). The well-known basic
                 knowledge of the conventional GAs is briefly presented.
                 The second part of the paper discusses an example of
                 optimisation of the design of the flexible
                 manufacturing system (FMS) in one row with GAs. First
                 the reasons for studying the layout of devices in the
                 FMS are discussed. The GA model, the most suitable way
                 of coding the solutions into the organisms and the
                 selected evolutionary and genetic operators are
                 presented. In the model, the automated guided vehicles
                 (AGVs) for transport between components of the FMS were
                 used. In this connection, the most favourable sequence
                 of devices in the row is established by means of GAs.
                 In the end the test results of the application made and
                 the analysis are discussed.",
  notes =        "Broken Jan 2013
                 http://www.eng.utt.ro/auif/rev/issue/no-05/no-05.html

                 University of Maribor, Faculty for Mechanical
                 Engineering, Laboratory for Intelligent Manufacturing
                 Systems",
}

Genetic Programming entries for Mirko Ficko Miha Kovacic Miran Brezocnik

Citations