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Statements

Subject Item
n2:RIV%2F00216305%3A26210%2F02%3APU31526%21RIV%2F2003%2FMSM%2F262103%2FN
rdf:type
n5:Vysledek skos:Concept
dcterms:description
The network Steiner tree problem (or Steiner tree problem in graphs) finds a shortest tree spanning a given vertex subset within a network. For exact solutions, a mixed integer programming model is proposed and checked in GAMS optimization package. However, the studied problem is NP-complete and therefore, for large scaled instances, the optimal solution cannot be found in a reasonable amount of time. In this case it is usually solved by approximation or deterministic heuristic methods. This paper propooses an approach that is based on simple approximations in a hybrid combination with stochastic heuristic methods (genetic algorithms and simulated annealing) applied to a binary string representation of Steiner vertex candidates. These methods are tested on standard benchmarks from OR-Library and suitable parameter settings are recommended to achieve good solutions. It was shown that by this approach, we can achieve near-optimal results for instances of up to 100 vertices, 200 edges and 50 terminals in The network Steiner tree problem (or Steiner tree problem in graphs) finds a shortest tree spanning a given vertex subset within a network. For exact solutions, a mixed integer programming model is proposed and checked in GAMS optimization package. However, the studied problem is NP-complete and therefore, for large scaled instances, the optimal solution cannot be found in a reasonable amount of time. In this case it is usually solved by approximation or deterministic heuristic methods. This paper propooses an approach that is based on simple approximations in a hybrid combination with stochastic heuristic methods (genetic algorithms and simulated annealing) applied to a binary string representation of Steiner vertex candidates. These methods are tested on standard benchmarks from OR-Library and suitable parameter settings are recommended to achieve good solutions. It was shown that by this approach, we can achieve near-optimal results for instances of up to 100 vertices, 200 edges and 50 terminals in
dcterms:title
Metaheuristics for the Network Steiner Tree Problem Metaheuristics for the Network Steiner Tree Problem
skos:prefLabel
Metaheuristics for the Network Steiner Tree Problem Metaheuristics for the Network Steiner Tree Problem
skos:notation
RIV/00216305:26210/02:PU31526!RIV/2003/MSM/262103/N
n3:strany
525-538
n3:aktivita
n14:Z
n3:aktivity
Z(MSM 261100009), Z(MSM 262100024)
n3:dodaniDat
n17:2003
n3:domaciTvurceVysledku
n7:1920863
n3:druhVysledku
n19:C
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n20:predkladatel
n3:idSjednocenehoVysledku
653031
n3:idVysledku
RIV/00216305:26210/02:PU31526
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Minimum spanning tree, Steiner tree problem, metaheuristic, genetic algorithm, simulated annealing
n3:klicoveSlovo
n4:Minimum%20spanning%20tree n4:simulated%20annealing n4:genetic%20algorithm n4:metaheuristic n4:Steiner%20tree%20problem
n3:kontrolniKodProRIV
[F1CCFF318313]
n3:mistoVydani
Wien (Austria)
n3:nazevEdiceCisloSvazku
DAAAM International Scientific Books
n3:nazevZdroje
Katalinic, B. (ed.): DAAAM International Scientific Book
n3:obor
n15:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:pocetUcastnikuAkce
0
n3:pocetZahranicnichUcastnikuAkce
0
n3:rokUplatneniVysledku
n17:2002
n3:tvurceVysledku
Šeda, Miloš
n3:zamer
n9:MSM%20262100024 n9:MSM%20261100009
s:numberOfPages
14
n18:hasPublisher
DAAAM International, Wien
n11:isbn
3-901509-30-5
n6:organizacniJednotka
26210