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Statements

Subject Item
n2:RIV%2F61989100%3A27740%2F14%3A86092833%21RIV15-MSM-27740___
rdf:type
n8:Vysledek skos:Concept
dcterms:description
Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms have attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving real world optimization problems. Swarm-inspired optimization has recently become very popular. Both ACO and PSO are successfully applied in the Traveling Salesman Problem (TSP). Our approach consists in combining Fuzzy Logic with ACO (FACO - Fuzzy Ant Colony Optimization) and PSO (FPSO - Fuzzy Particle Swarm Optimization) for solving the TSP. Experimental results and comparative studies illustrate the importance of Fuzzy logic in reducing the time and the best length for the TSP problems considered. 2013 IEEE. Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms have attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving real world optimization problems. Swarm-inspired optimization has recently become very popular. Both ACO and PSO are successfully applied in the Traveling Salesman Problem (TSP). Our approach consists in combining Fuzzy Logic with ACO (FACO - Fuzzy Ant Colony Optimization) and PSO (FPSO - Fuzzy Particle Swarm Optimization) for solving the TSP. Experimental results and comparative studies illustrate the importance of Fuzzy logic in reducing the time and the best length for the TSP problems considered. 2013 IEEE.
dcterms:title
Hybridization of Fuzzy PSO and Fuzzy ACO applied to TSP Hybridization of Fuzzy PSO and Fuzzy ACO applied to TSP
skos:prefLabel
Hybridization of Fuzzy PSO and Fuzzy ACO applied to TSP Hybridization of Fuzzy PSO and Fuzzy ACO applied to TSP
skos:notation
RIV/61989100:27740/14:86092833!RIV15-MSM-27740___
n3:aktivita
n17:P
n3:aktivity
P(ED1.1.00/02.0070)
n3:dodaniDat
n11:2015
n3:domaciTvurceVysledku
Abraham Padath, Ajith
n3:druhVysledku
n4:D
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n14:predkladatel
n3:idSjednocenehoVysledku
20048
n3:idVysledku
RIV/61989100:27740/14:86092833
n3:jazykVysledku
n20:eng
n3:klicovaSlova
Traveling Salesman Problem; Swarm intelligence; Fuzzy Particle Swarm Optimization; Fuzzy Ant Colony Optimization
n3:klicoveSlovo
n7:Fuzzy%20Particle%20Swarm%20Optimization n7:Swarm%20intelligence n7:Fuzzy%20Ant%20Colony%20Optimization n7:Traveling%20Salesman%20Problem
n3:kontrolniKodProRIV
[2DD08AFCD269]
n3:mistoKonaniAkce
Yassmine Hammamet
n3:mistoVydani
New York
n3:nazevZdroje
Proceedings of the 2013 Thirteenth International Conference on Hybrid Intelligent Systems (HIS 2013) : Yassmine Hammamet, Tunisia, 04-06 December, 2013
n3:obor
n21:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
4
n3:projekt
n19:ED1.1.00%2F02.0070
n3:rokUplatneniVysledku
n11:2014
n3:tvurceVysledku
Alimi, A. M. Abraham Padath, Ajith Baklouti, N. Elloumi, W.
n3:typAkce
n15:WRD
n3:zahajeniAkce
2013-12-04+01:00
s:numberOfPages
6
n10:doi
10.1109/HIS.2013.6920464
n6:hasPublisher
IEEE
n9:isbn
978-1-4799-2439-4
n12:organizacniJednotka
27740