Communication network design using particle swarm optimization

Papagianni, C; Papadopoulos, K; Pappas, C; Tselikas, ND; Kaklamani, DT; Venieris, IS

dc.contributor.author	Papagianni, C	en
dc.contributor.author	Papadopoulos, K	en
dc.contributor.author	Pappas, C	en
dc.contributor.author	Tselikas, ND	en
dc.contributor.author	Kaklamani, DT	en
dc.contributor.author	Venieris, IS	en
dc.date.accessioned	2014-03-01T02:45:11Z
dc.date.available	2014-03-01T02:45:11Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32190
dc.subject	Community Networks	en
dc.subject	Design Process	en
dc.subject	Network Design	en
dc.subject	Packet Delay	en
dc.subject	particle swarm optimizer	en
dc.subject	Premature Convergence	en
dc.subject	Quality of Service Issue	en
dc.subject	Particle Swarm Optimization Algorithm	en
dc.subject.other	Average packet delays	en
dc.subject.other	Communication networks	en
dc.subject.other	Design process	en
dc.subject.other	Evolutionary approach	en
dc.subject.other	Hybrid particle swarm optimization algorithm	en
dc.subject.other	Hybrid PSO	en
dc.subject.other	Multi objective	en
dc.subject.other	Multi-criteria	en
dc.subject.other	Network design problems	en
dc.subject.other	Network infrastructure	en
dc.subject.other	Network layout	en
dc.subject.other	Premature convergence	en
dc.subject.other	Single objective	en
dc.subject.other	Computer science	en
dc.subject.other	Design	en
dc.subject.other	Information technology	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Quality of service	en
dc.subject.other	Particle swarm optimization (PSO)	en
dc.title	Communication network design using particle swarm optimization	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IMCSIT.2008.4747351	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IMCSIT.2008.4747351	en
heal.identifier.secondary	4747351	en
heal.publicationDate	2008	en
heal.abstract	Particle Swarm Optimization is applied on an instance of single and multi criteria network design problem. The primary goal of this study is to present the efficiency of a simple hybrid particle swarm optimization algorithm on the design of a network infrastructure including decisions concerning the locations and sizes of links. A complementary goal is to also address Quality of Service issues in the design process. Optimization objectives in this case are the network layout cost and the average packet delay in the network Therefore a multi-objective instance of the hybrid PSO algorithm is applied. The particular hybrid PSO includes mutation to avoid premature convergence. For the same reason repulsion/attraction mechanisms are also applied on the single objective case. Mutation is passed on to the multi-objective instance of the algorithm. Obtained results are compared with corresponding evolutionary approaches.© 2008 IEEE.	en
heal.journalName	Proceedings of the International Multiconference on Computer Science and Information Technology, IMCSIT 2008	en
dc.identifier.doi	10.1109/IMCSIT.2008.4747351	en
dc.identifier.volume	3	en
dc.identifier.spage	915	en
dc.identifier.epage	920	en