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Optimizing Hub-And-Spoke Networks Under Demand Uncertainty: A Stochastic Capacitated Single Allocation P-Hub Covering Model with Lagrangian Relaxation
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چکیده: (409 مشاهده) |
Traditional maximal p-hub covering problems focus on scenarios where network flow is constrained by resource limitations. However, many existing models rely on static parameters, overlooking the inherent randomness present in real-world logistics. This oversight can result in suboptimal network designs that are vulnerable to congestion and rising costs as demand varies. To address this issue, we propose a novel mathematical model for the capacitated single allocation maximal p-hub covering problem that takes into account stochastic variations in origin-destination flows. Although solving this model poses computational challenges, we utilize a Lagrangian relaxation algorithm to enhance efficiency. Computational experiments using the CAB dataset highlight the effectiveness of our approach in achieving optimal solutions while reducing computation time. This framework offers valuable insights for designing robust hub-and-spoke networks in the face of demand uncertainty.
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متن کامل [PDF 310 kb]
(610 دریافت)
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نوع مطالعه: پژوهشی |
موضوع مقاله:
Mathematical Modeling and Applications of OR
دریافت: 1403/3/20 | پذیرش: 1403/5/31 | انتشار: 1403/6/12
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