Generalized Short-stage Multichannel Queuing Models Using Genetic Algorithms: A Real-World Application to Seaports
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{tsakonas_generalized_2001,
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author = "Athanasios Tsakonas and Helen Kitrinou and
Georgios Dounias",
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title = "Generalized Short-stage Multichannel Queuing Models
Using Genetic Algorithms: A Real-World Application to
Seaports",
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journal = "Journal of Management Sciences and Regional
Development",
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year = "2001",
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volume = "3",
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pages = "215--231",
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month = jul,
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keywords = "genetic algorithms, genetic programming, computational
intelligence, queuing systems, seaport operating cost
optimization, transportation problems",
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ISSN = "1107-9819",
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publisher = "Constantine Porphyrogenetus International
Association",
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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",
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URL = "https://pdfs.semanticscholar.org/7f32/d6de7a91d93e352489a7c19652f1e196f9bf.pdf",
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size = "17 pages",
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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.",
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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