Job shop scheduling problem with heuristic genetic programming operators

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

  author =       "Lukas Povoda and Radim Burget and Jan Masek and 
                 Malay Kishore Dutta",
  booktitle =    "2nd International Conference on Signal Processing and
                 Integrated Networks (SPIN)",
  title =        "Job shop scheduling problem with heuristic genetic
                 programming operators",
  year =         "2015",
  pages =        "702--707",
  abstract =     "This paper introduces an optimisation algorithm for
                 job shop scheduling problem in logistic warehouses. The
                 algorithm is based on genetic programming and uses
                 parallel processing. For better performance a new
                 optimisation method called 'priority rules' was
                 proposed. We found out that the three proposed priority
                 rules help algorithm to prevent stuck in the local
                 optima and get better results from genetic programming
                 optimisation. Algorithm was tested with batch of tests
                 based on data from real warehouse and with synthetic
                 tests generated randomly (inspired by the real world
                 scenarios). The results indicate interesting reduction
                 of time that is necessary to fulfil all tasks in
                 warehouses, reduction in number of collisions and
                 better optimisation performance.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/SPIN.2015.7095307",
  month =        feb,
  notes =        "Faculty of Electrical Engineering and Communication,
                 Brno University of Technology, Brno, Czech

                 Also known as \cite{7095307}",

Genetic Programming entries for Lukas Povoda Radim Burget Jan Masek Malay Kishore Dutta