Decomposition methods for the two-stage stochastic Steiner tree problem

Leitner, Markus; Ljubić, Ivana; Luipersbeck, Martin; Sinnl, Markus

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1007/s10589-017-9966-x

Titre :

Decomposition methods for the two-stage stochastic Steiner tree problem

Auteur(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]

Titre de la revue :

Computational Optimization and Applications

Pagination :

1-40

Éditeur :

Springer Verlag

Date de publication :

2017

ISSN :

0926-6003

Discipline(s) HAL :

Computer Science [cs]/Operations Research [math.OC]

Résumé en anglais : [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 ...
Lire la suite >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.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :