Hierarchical clustering-based allocation in location models

L. Nácher, M. Baldomero Naranjo, M. Landete, M. Leal

This work presents a novel mixed integer linear programming framework that integrates facility location with the simultaneous construction of hierarchical clustering. By using a distance matrix for location and a dissimilarity matrix for clustering, the model captures the interdependence between where facilities are placed and the hierarchical clustering structures that emerge within the groups assigned to each facility. Several formulations are developed to incorporate single-linkage and complete-linkage clustering in the location-allocation problem, enabling a comparative analysis of how different hierarchical criteria influence the integrated problem. The approach is validated through a case study that illustrates its behavior and the consistency between the assignment decisions and the resulting hierarchical structure.

Keywords: Facility location, Hierarchical clustering, Mixed-integer programming

GT GELOCA 3: Covering models and clustering approaches in location
September 4, 2026  11:10 AM
Aula B

A. MANCUSO, A. M. Rodríguez Chía, F. Saldanha-da-Gama, C. Sterle

C. Domínguez-Bravo, E. Fernández, A. Lüer Villagra

D. Amitrano, M. Baldomero Naranjo, M. Boccia, A. Mancuso, A. Masone, A. M. Rodríguez Chía, C. Sterle

C. Valverde Martín, J. Puerto Albandoz, L. Amorosi, P. Dell'Olmo