Metaheuristics for the Network Steiner Tree Problem
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F02%3APU31526" target="_blank" >RIV/00216305:26210/02:PU31526 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Metaheuristics for the Network Steiner Tree Problem
Popis výsledku v původním jazyce
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
Název v anglickém jazyce
Metaheuristics for the Network Steiner Tree Problem
Popis výsledku anglicky
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
Klasifikace
Druh
C - Kapitola v odborné knize
CEP obor
BB - Aplikovaná statistika, operační výzkum
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
Z - Vyzkumny zamer (s odkazem do CEZ)
Ostatní
Rok uplatnění
2002
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název knihy nebo sborníku
Katalinic, B. (ed.): DAAAM International Scientific Book
ISBN
3-901509-30-5
Počet stran výsledku
14
Strana od-do
525-538
Počet stran knihy
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Název nakladatele
DAAAM International, Wien
Místo vydání
Wien (Austria)
Kód UT WoS kapitoly
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