Decomposition methods for the two-stage ...
Document type :
Article dans une revue scientifique: Article original
Title :
Decomposition methods for the two-stage stochastic Steiner tree problem
Author(s) :
Leitner, Markus [Auteur]
Universität Wien = University of Vienna
Ljubić, Ivana [Auteur]
ESSEC Business School
Luipersbeck, Martin [Auteur]
Universität Wien = University of Vienna
Sinnl, Markus [Auteur]
Universität Wien = University of Vienna
Integrated Optimization with Complex Structure [INOCS]
Universität Wien = University of Vienna
Ljubić, Ivana [Auteur]
ESSEC Business School
Luipersbeck, Martin [Auteur]
Universität Wien = University of Vienna
Sinnl, Markus [Auteur]
Universität Wien = University of Vienna
Integrated Optimization with Complex Structure [INOCS]
Journal title :
Computational Optimization and Applications
Pages :
1-40
Publisher :
Springer Verlag
Publication date :
2017
ISSN :
0926-6003
HAL domain(s) :
Computer Science [cs]/Operations Research [math.OC]
English abstract : [en]
A new algorithmic approach for solving the stochastic Steiner tree problem based on three procedures for computing lower bounds (dual ascent, Lagrangian relaxation, Benders decomposition) is introduced. Our method is derived ...
Show more >A new algorithmic approach for solving the stochastic Steiner tree problem based on three procedures for computing lower bounds (dual ascent, Lagrangian relaxation, Benders decomposition) is introduced. Our method is derived from a new integer linear programming formulation, which is shown to be strongest among all known formulations. The resulting method, which relies on an interplay of the dual information retrieved from the respective dual procedures, computes upper and lower bounds and combines them with several rules for fixing variables in order to decrease the size of problem instances. The effectiveness of our method is compared in an extensive computational study with the state-of-the-art exact approach, which employs a Benders decomposition based on two-stage branch-and-cut, and a genetic algorithm introduced during the DIMACS implementation challenge on Steiner trees. Our results indicate that the presented method significantly outperforms existing ones, both on benchmark instances from literature, as well as on large-scale telecommunication networks.Show less >
Show more >A new algorithmic approach for solving the stochastic Steiner tree problem based on three procedures for computing lower bounds (dual ascent, Lagrangian relaxation, Benders decomposition) is introduced. Our method is derived from a new integer linear programming formulation, which is shown to be strongest among all known formulations. The resulting method, which relies on an interplay of the dual information retrieved from the respective dual procedures, computes upper and lower bounds and combines them with several rules for fixing variables in order to decrease the size of problem instances. The effectiveness of our method is compared in an extensive computational study with the state-of-the-art exact approach, which employs a Benders decomposition based on two-stage branch-and-cut, and a genetic algorithm introduced during the DIMACS implementation challenge on Steiner trees. Our results indicate that the presented method significantly outperforms existing ones, both on benchmark instances from literature, as well as on large-scale telecommunication networks.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
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