Artikel

Robust uncapacitated multiple allocation hub location problem under demand uncertainty: Minimization of cost deviations

The hub location-allocation problem under uncertainty is a real-world task arising in the areas such as public and freight transportation and telecommunication systems. In many applications, the demand is considered as inexact because of the forecasting inaccuracies or human's unpredictability. This study addresses the robust uncapacitated multiple allocation hub location problem with a set of demand scenarios. The problem is formulated as a nonlinear stochastic optimization problem to minimize the hub installation costs, expected transportation costs and expected absolute deviation of transportation costs. To eliminate the nonlinearity, the equivalent linear problem is introduced. The expected absolute deviation is the robustness measure to derive the solution close to each scenario. The robust hub location is assumed to deliver the least costs difference across the scenarios. The number of scenarios increases size and complexity of the task. Therefore, the classical and improved Benders decomposition algorithms are applied to achieve the best computational performance. The numerical experiment on CAB and AP dataset presents the difference of resulting hub networks in stochastic and robust formulations. Furthermore, performance of two Benders decomposition strategies in comparison with Gurobi solver is assessed and discussed.

Language
Englisch

Bibliographic citation
Journal: Journal of Industrial Engineering International ; ISSN: 2251-712X ; Volume: 15 ; Year: 2019 ; Issue: S1 ; Pages: 199-207 ; Heidelberg: Springer

Classification
Management
Subject
Hub location problem
Stochastic programming
Absolute deviation
Robust solution
Benders decomposition
Pareto-optimal cuts

Event
Geistige Schöpfung
(who)
Lozkins, Aleksejs
Krasilnikov, Mikhail
Bure, Vladimir
Event
Veröffentlichung
(who)
Springer
(where)
Heidelberg
(when)
2019

DOI
doi:10.1007/s40092-019-00329-9
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Lozkins, Aleksejs
  • Krasilnikov, Mikhail
  • Bure, Vladimir
  • Springer

Time of origin

  • 2019

Other Objects (12)