Hub location problems with asymmetric allocation
I. Espejo (1), M. Landete (2), M. Leal (2), A. Mar\'in (3) ((1) Departamento de Estad\'istica e Investigaci\'on Operativa, Universidad de C\'adiz, Spain, (2) Centro de Investigaci\'on Operativa, Universidad Miguel Hern\'andez, Spain

TL;DR
This paper introduces the asymmetric hub location problem (r,s)-AHLP, addressing real-world flow asymmetries with new formulations and solution methods, expanding hub location theory's applicability.
Contribution
It proposes novel integer programming models for (r,s)-AHLP, including a compact formulation with improved efficiency and effectiveness, supported by valid inequalities and decomposition techniques.
Findings
The new models outperform classical symmetric models in computational tests.
The compact formulation reduces problem size and improves solution quality.
The methodology effectively solves standard benchmark datasets.
Abstract
Hub location problems are central to optimizing logistics, telecommunications, and transportation networks by consolidating flows through strategically placed hubs. While existing models assume symmetric allocation, where hubs handle incoming and outgoing flows uniformly, real-world applications often require asymmetric handling of origins and destinations. This paper introduces the Asymmetric Hub Location Problem ((r,s)-AHLP), a novel framework where origins and destinations may connect to hubs under distinct allocation limits (r and s, respectively). We then focus on the (1,p)-AHLP variant, where origins are single-assigned and destinations are multi-assigned, motivated by applications in humanitarian logistics and global supply chains (e.g., UN relief networks, e-commerce fulfillment). We propose two integer programming formulations: A four-index adaptation of classical models and…
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