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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F14%3A86092780%21RIV15-MSM-27240___
rdf:type
skos:Concept n15:Vysledek
dcterms:description
An Ikeda map embedded genetic algorithm is in- troduced in this research in order to solve the order picking problem. The chaos based algorithm is compared against the canonical pseudo-random number based genetic algorithm over thirty test instances of varying complexity. From the results, the chaos based genetic algorithm is shown to have better overall performance, especially for larger sized problem instances. The statistical paired t-test comparison of the results further reinforces the fact that the chaos based genetic algorithm is significantly better performing. An Ikeda map embedded genetic algorithm is in- troduced in this research in order to solve the order picking problem. The chaos based algorithm is compared against the canonical pseudo-random number based genetic algorithm over thirty test instances of varying complexity. From the results, the chaos based genetic algorithm is shown to have better overall performance, especially for larger sized problem instances. The statistical paired t-test comparison of the results further reinforces the fact that the chaos based genetic algorithm is significantly better performing.
dcterms:title
A genetic algorithm with an embedded Ikeda map applied to an order picking problem in a multi-aisle warehouse A genetic algorithm with an embedded Ikeda map applied to an order picking problem in a multi-aisle warehouse
skos:prefLabel
A genetic algorithm with an embedded Ikeda map applied to an order picking problem in a multi-aisle warehouse A genetic algorithm with an embedded Ikeda map applied to an order picking problem in a multi-aisle warehouse
skos:notation
RIV/61989100:27240/14:86092780!RIV15-MSM-27240___
n3:aktivita
n17:S n17:P
n3:aktivity
P(GA13-08195S), S
n3:dodaniDat
n16:2015
n3:domaciTvurceVysledku
Davendra, Donald David
n3:druhVysledku
n9:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n18:predkladatel
n3:idSjednocenehoVysledku
749
n3:idVysledku
RIV/61989100:27240/14:86092780
n3:jazykVysledku
n14:eng
n3:klicovaSlova
Genetic algorithm, Ikeda map, order picking problem
n3:klicoveSlovo
n6:order%20picking%20problem n6:Genetic%20algorithm n6:Ikeda%20map
n3:kontrolniKodProRIV
[FD94433AAB8C]
n3:mistoKonaniAkce
Orlando
n3:mistoVydani
New York
n3:nazevZdroje
IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIPLS 2014: 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, Proceedings
n3:obor
n12:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
5
n3:projekt
n5:GA13-08195S
n3:rokUplatneniVysledku
n16:2014
n3:tvurceVysledku
Davendra, Donald David Stauffer, Michael Hanne, Thomas Dornberger, Rolf Ryter, Remo
n3:typAkce
n21:WRD
n3:zahajeniAkce
2014-12-09+01:00
s:numberOfPages
6
n11:doi
10.1109/CIPLS.2014.7007161
n4:hasPublisher
Institute of Electrical and Electronics Engineers
n19:isbn
978-1-4799-4501-6
n10:organizacniJednotka
27240