Genetic Programming Heuristics for Multiple Machine Scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Domagoj Jakobovi\'c and Leonardo Jelenkovi\'c and 
                 Leo Budin",
  title =        "Genetic Programming Heuristics for Multiple Machine
  editor =       "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and 
                 Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
  booktitle =    "Proceedings of the 10th European Conference on Genetic
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "4445",
  year =         "2007",
  address =      "Valencia, Spain",
  month =        "11-13 " # apr,
  pages =        "321--330",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-71602-5",
  isbn13 =       "978-3-540-71602-0",
  DOI =          "doi:10.1007/978-3-540-71605-1_30",
  abstract =     "In this paper we present a method for creating
                 scheduling heuristics for parallel proportional machine
                 scheduling environment and arbitrary performance
                 criteria. Genetic programming is used to synthesise the
                 priority function which, coupled with an appropriate
                 meta-algorithm for a given environment, forms the
                 priority scheduling heuristic. We show that the
                 procedures derived in this way can perform similarly or
                 better than existing algorithms. Additionally, this
                 approach may be particularly useful for those
                 combinations of scheduling environment and criteria for
                 which there are no adequate scheduling algorithms.",
  notes =        "Part of \cite{ebner:2007:GP} EuroGP'2007 held in
                 conjunction with EvoCOP2007, EvoBIO2007 and

Genetic Programming entries for Domagoj Jakobovic Leonardo Jelenkovic Leo Budin