Artikel
Scenario-based modeling for multiple allocation hub location problem under disruption risk: multiple cuts Benders decomposition approach
The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of scenarios grows exponentially with the number of facilities. To alleviate this issue, two approaches are applied simultaneously. The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. Then, by applying the multiple cuts Benders decomposition approach, computational performance is enhanced. Numerical studies show the effective performance of the SAA in terms of optimality gap for small problem instances with numerous scenarios. Moreover, performance of multi-cut Benders decomposition is assessed through comparison with the classic version and the computational results reveal the superiority of the multi-cut approach regarding the computational time and number of iterations.
- Sprache
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Englisch
- Erschienen in
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Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 13 ; Year: 2017 ; Issue: 4 ; Pages: 445-453 ; Heidelberg: Springer
- Klassifikation
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Management
- Thema
-
Reliable hub location problem
Two-stage stochastic programming
Sample average approximation
Multiple cuts
Benders decomposition
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Yahyaei, Mohsen
Bashiri, Mahdi
- Ereignis
-
Veröffentlichung
- (wer)
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Springer
- (wo)
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Heidelberg
- (wann)
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2017
- DOI
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doi:10.1007/s40092-017-0195-9
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Yahyaei, Mohsen
- Bashiri, Mahdi
- Springer
Entstanden
- 2017
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