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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{tsakonas_generalized_2001,

• author = "Athanasios Tsakonas and Helen Kitrinou and Georgios Dounias",
• title = "Generalized Short-stage Multichannel Queuing Models Using Genetic Algorithms: A Real-World Application to Seaports",
• journal = "Journal of Management Sciences and Regional Development",
• 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 Association",
• URL = "http://www.stt.aegean.gr/geopolab/_private/MANAGEMENT%20SCIENCES%20AND%20REGIONAL%20DEVELOPMENT%203%20-%20Tsakonas%20Kitrinou%20Dounias%20-%20Shortstage%20multichannel%20queuing%20models%20genetic%20algorithms.%20Seaports.pdf",
• URL = "https://pdfs.semanticscholar.org/7f32/d6de7a91d93e352489a7c19652f1e196f9bf.pdf",
• 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 http://www.stt.aegean.gr/geopolab/Journal%20of%20Management%20Sciences%20and%20Regional%20Development.htm",

}

Genetic Programming entries for Athanasios D Tsakonas Helen Kitrinou Georgios Dounias

Citations