Evolutionary generation of dispatching rule sets for complex dynamic scheduling problems

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

@Article{Pickardt:2012:IJPE,
  author =       "Christoph W. Pickardt and Torsten Hildebrandt and 
                 Jurgen Branke and Jens Heger and Bernd Scholz-Reiter",
  title =        "Evolutionary generation of dispatching rule sets for
                 complex dynamic scheduling problems",
  journal =      "International Journal of Production Economics",
  year =         "2013",
  volume =       "145",
  number =       "1",
  pages =        "67--77",
  ISSN =         "0925-5273",
  DOI =          "doi:10.1016/j.ijpe.2012.10.016",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0925527312004574",
  abstract =     "We propose a two-stage hyper-heuristic for the
                 generation of a set of work centre-specific dispatching
                 rules. The approach combines a genetic programming (GP)
                 algorithm that evolves a composite rule from basic job
                 attributes with an evolutionary algorithm (EA) that
                 searches for a good assignment of rules to work
                 centres. The hyper-heuristic is tested against its two
                 components and rules from the literature on a complex
                 dynamic job shop problem from semiconductor
                 manufacturing. Results show that all three
                 hyper-heuristics are able to generate (sets of) rules
                 that achieve a significantly lower mean weighted
                 tardiness than any of the benchmark rules. Moreover,
                 the two-stage approach proves to outperform the GP and
                 EA hyper-heuristic as it optimises on two different
                 heuristic search spaces that appear to tap different
                 optimisation potentials. The resulting rule sets are
                 also robust to most changes in the operating
                 conditions.",
  keywords =     "genetic algorithms, genetic programming,
                 Hyper-heuristics, Dispatching rules, Production
                 scheduling, Semiconductor manufacturing, Evolutionary
                 algorithms",
}

Genetic Programming entries for Christoph Pickardt Torsten Hildebrandt Jurgen Branke Jens Heger Bernd Scholz-Reiter

Citations