An Efficient Approach for Solving Hub Location Problems Using Network Autocorrelation Structures

Changwha Oh, Hyun Kim and Yongwan Chun

Annals of the American Association of Geographers, 2025, vol. 115, issue 6, 1263-1285

Abstract: The properties of spatial information have been shown to aid in identifying optimal solutions for location–allocation problems. Little effort, though, has been made to develop a spatially informed approach to solving hub location problems, as this class of problems entails a more complex model structure and greater challenges in terms of solving capability. To address this issue, this research proposes the spatially informed hub location problem (SI-HLP), derived from investigating the behavior of hub location problems in determining hubs and their allocations to nonhubs to achieve optimal solutions leveraged by underlying spatial characteristics among nodes, links, and routes. The performance of SI-HLP is achieved with two strategies to distinguish essential and nonessential decision variables for location and allocation decision variables, using an innovative convex-hull-based method, HUBI-COV, to capture nodes with high positive network autocorrelations and their allocated links. Simulation experiments under robustly designed settings were conducted to generalize the findings and assess the effectiveness of SI-HLP, indicating that SI-HLPs provide a novel avenue for advancing the solution of large-scale hub location problems.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/24694452.2025.2482105 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:raagxx:v:115:y:2025:i:6:p:1263-1285

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/raag21

DOI: 10.1080/24694452.2025.2482105

Access Statistics for this article

Annals of the American Association of Geographers is currently edited by Jennifer Cassidento

More articles in Annals of the American Association of Geographers from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().