Generalized Short-stage Multichannel Queuing Models Using Genetic Algorithms: A Real-World Application to Seaports

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Athanasios Tsakonas and Helen Kitrinou and 
                 Georgios Dounias",
  title =        "Generalized Short-stage Multichannel Queuing Models
                 Using Genetic Algorithms: A Real-World Application to
  journal =      "Journal of Management Sciences and Regional
  year =         "2001",
  volume =       "3",
  pages =        "215--231",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, computational
                 intelligence, queuing systems, seaport operating cost
                 optimization, transportation problems",
  ISSN =         "1107-9819",
  publisher =    "Constantine Porphyrogenetus International
  URL =          "",
  URL =          "",
  size =         "17 pages",
  abstract =     "This paper introduces genetic algorithms for inducing
                 high-level knowledge from available domain data,
                 succeeding to obtain generalized solutions for a
                 short-stage multi-channel queuing model. The domain of
                 application, refers to the transportation problem of
                 transit storage and reload in seaports. Specifically,
                 when a ship approaches the port, can be served by more
                 than one service channel, in other words the seaport
                 represents a queuing system. The seaport system
                 forwards ships and lorries into the port, moves
                 vehicles and cranes between two positions i.e.
                 warehouses and berths, and finally loads and unloads
                 cargoes from ships and lorries. Between the two
                 load/unload processes taking place in both, ships and
                 lorries the transit storage process is embedded, thus
                 forming in fact a three stage multi-channel queuing
                 system. The standard process of working with such a
                 queuing problem supposes Poisson distribution in all
                 the service stages, definition of the service and
                 waiting costs and the construction of an objective
                 function for finding the best-cost solution. The
                 solution produced above is generalized by applying a
                 genetic algorithm approach for finding the best seaport
                 configuration (i.e. optimal number of cranes,
                 warehouses and lorries needed) among a possible set of
                 them, which will offer the minimum seaport operating
                 cost. The paper demonstrates that, when a set of
                 possible configurations is effectively coded into a
                 genetic population, the best solution might be achieved
                 in a reasonably short time and well approximated.",
  notes =        "MSRD

Genetic Programming entries for Athanasios D Tsakonas Helen Kitrinou Georgios Dounias