Double-Deck Elevator Systems Adaptive to Traffic Flows Using Genetic Network Programming

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

@InProceedings{Zhou2:2008:cec,
  author =       "Jin Zhou and Lu Yu and Shingo Mabu and 
                 Kaoru Shimada and Kotaro Hirasawa and Sandor Markon",
  title =        "Double-Deck Elevator Systems Adaptive to Traffic Flows
                 Using Genetic Network Programming",
  booktitle =    "2008 IEEE World Congress on Computational
                 Intelligence",
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "773--778",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0198.pdf",
  DOI =          "doi:10.1109/CEC.2008.4630883",
  abstract =     "Double-deck elevator system (DDES) has been invented
                 firstly as a solution to improve the transportation
                 capacity of elevator group systems in the up-peak
                 traffic pattern. The transportation capacity could be
                 even doubled when DDES runs in a pure up-peak traffic
                 pattern where two connected cages stop at every two
                 floors in an elevator round trip. However, the specific
                 features of DDES make the elevator system intractable
                 when it runs in some other traffic patterns. Moreover,
                 since almost all of the traffic flows vary continuously
                 during a day, an optimised controller of DDES is
                 required to adapt the varying traffic flow. In this
                 paper, we have proposed a controller adaptive to
                 traffic flows for DDES using Genetic Network
                 Programming (GNP) based on our past studies in this
                 field, where the effectiveness of DDES controller using
                 GNP has been verified in three typical traffic
                 patterns. A traffic flow judgement part was introduced
                 into the GNP framework of DDES controller, and the
                 different parts of GNP were expected to be functionally
                 localised by the evolutionary process to make the
                 appropriate cage assignment in different traffic flow
                 patterns. Simulation results show that the proposed
                 method outperforms a conventional approach and two
                 heuristic approaches in a varying traffic flow during
                 the work time of a typical office building.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",
}

Genetic Programming entries for Jin Zhou Lu Yu Shingo Mabu Kaoru Shimada Kotaro Hirasawa Sandor Markon

Citations