Automatic design of scheduling rules for complex manufacturing systems by multi-objective simulation-based optimization

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Freitag:2016:AMT,
  author =       "Michael Freitag and Torsten Hildebrandt",
  title =        "Automatic design of scheduling rules for complex
                 manufacturing systems by multi-objective
                 simulation-based optimization",
  journal =      "\{CIRP\} Annals - Manufacturing Technology",
  volume =       "65",
  number =       "1",
  pages =        "433--436",
  year =         "2016",
  ISSN =         "0007-8506",
  DOI =          "doi:10.1016/j.cirp.2016.04.066",
  URL =          "http://www.sciencedirect.com/science/article/pii/S000785061630066X",
  abstract =     "Complex manufacturing systems pose challenges for
                 production planning and control. Amongst other
                 objectives, orders have to be finished according to
                 their due-dates. However, avoiding both earliness and
                 tardiness requires a high level of process control.
                 This article describes the use of simulation-based
                 multi-objective optimization (multi-objective Genetic
                 Programming) as a hyper-heuristic to automatically
                 develop improved dispatching rules specifically for
                 this control problem. Using a complex manufacturing
                 scenario from semiconductor manufacturing as an
                 example, it is shown that the resulting rules
                 significantly outperform state-of-the-art dispatching
                 rules from literature.",
  keywords =     "genetic algorithms, genetic programming, Manufacturing
                 systems, Scheduling, Hyper-heuristic",
}

Genetic Programming entries for Michael Freitag Torsten Hildebrandt

Citations