Constructing large-scale benchmark datasets for the hierarchical hub location problem using geospatial information: a case study on populous Indian cities.

ABSTRACT: This paper introduces an innovative approach for constructing large-scale, realistic benchmark geospatial datasets specifically designed for the single-allocation hierarchical hub median problem, a key variant of the hierarchical hub location problem. Addressing the lack of publicly available large-scale datasets in location science, we have provided a detailed step-by-step methodology to generate benchmark datasets. Also, we have provided datasets of various granularities based on Kolkata and Mumbai, two of India's most populous metropolitan cities as a ready reference. The datasets are built using actual building-level geographic data acquired from OpenStreetMap and QGIS. Benchmark datasets are solved for the single-allocation hierarchical hub median problem formulation using IBM ILOG CP

SUBMITTER: Bhattacharjee AK 

PROVIDER: S-EPMC12533260 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature