Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/325172 
Year of Publication: 
2022
Citation: 
[Journal:] EURO Journal on Transportation and Logistics (EJTL) [ISSN:] 2192-4384 [Volume:] 11 [Issue:] 1 [Article No.:] 100069 [Year:] 2022 [Pages:] 1-12
Publisher: 
Elsevier, Amsterdam
Abstract: 
We consider the robust single-source capacitated facility location problem with uncertainty in customer demands. A cardinality-constrained uncertainty set is assumed for the robust problem. To solve it efficiently, we propose an allocation-based formulation derived by Dantzig-Wolfe decomposition and a branch-and-price algorithm. The computational experiments show that our branch-and-price algorithm outperforms CPLEX in many cases, which solves the ordinary robust reformulation. We also examine the trade-off relationship between the empirical probability of infeasibility and the additional costs incurred and observe that the robustness of solutions can be improved significantly with small additional costs.
Subjects: 
Robust optimization
Single-source capacitated facility location problem
Demand uncertainty
Dantzig-Wolfe decomposition
Branch-and-price algorithm
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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