Application of gene expression programming on dynamic job shop scheduling problem

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Li Nie and Liang Gao and Peigen Li and Liping Zhang",
  title =        "Application of gene expression programming on dynamic
                 job shop scheduling problem",
  booktitle =    "15th International Conference on Computer Supported
                 Cooperative Work in Design (CSCWD 2011)",
  year =         "2011",
  pages =        "291--295",
  address =      "Lausanne",
  month =        "8-10 " # jun,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, GEP chromosome, dynamic job
                 shop scheduling problem, encoding scheme, evolutionary
                 principle, gene expression programming, job release
                 dates, scheduling rules, search technique, dynamic
                 scheduling, encoding, job shop scheduling, search
  isbn13 =       "978-1-4577-0386-7",
  DOI =          "doi:10.1109/CSCWD.2011.5960088",
  size =         "5 pages",
  abstract =     "In this paper, we consider a dynamic job shop
                 scheduling problem (DJSSP) with job release dates. In
                 such a problem, jobs arrive over time and are unknown
                 in advance and they can not be scheduled before their
                 arrivals. We apply gene expression programming (GEP), a
                 new search technique based on evolutionary principle,
                 on the scheduling problem to automatically construct
                 efficient scheduling rules (SRs), which can generate
                 high-quality schedules for the problem. A novel
                 encoding scheme is proposed which prevents the length
                 of chromosomes from increasing dramatically with the
                 increase of the size of scheduling problems. And a new
                 decoding scheme is also proposed which transfers a GEP
                 chromosome into a schedule for each problem instance.
                 The proposed GEP-based method is valuated for its
                 solution quality. According to computational experiment
                 results, the method is proved to be able to construct
                 effective SRs for DJSSP with job release dates.",
  notes =        "State Key Lab. of Digital Manuf. Equip. & Technol.,
                 Huazhong Univ. of Sci. & Technol., Wuhan, China Also
                 known as \cite{5960088}",

Genetic Programming entries for Li Nie Liang Gao Peigen Li Liping Zhang