The p-regions problem involves the aggregation or clustering of n small areas into p spatially-contiguous regions while optimizing some criteria. The main objective of this paper is to explore possible avenues for formulating this problem as a mixed integer programming problem (MIP). The critical issue in formulating this problem is to ensure that each region is a spatially contiguous cluster of small areas. We introduce three MIP models for solving the p-regions problem. Each model minimizes the sum of dissimilarities between all pairs of areas within each region while guaranteeing contiguity. Three strategies designed to ensure contiguity are presented: 1) an adaptation of Miller, Tucker, and Zemlin tour-breaking constraints developed for the traveling salesman problem; 2) the use of ordered-area assignment variables based upon an extension of an approach of Cova and Church for the geographical site design problem; and 3) the use of ow constraints based upon an extension of Shirabe. We test the efficacy of each formulation as well as specify a strategy to reduce overall problem size.
Infraestructura pública y precios de vivienda: Una aplicación de regresión geográficamente ponderada en el contexto de precios hedónicos.
Python library with spatially constrained clustering algorithms
Interactive tool for visualizing the interindustry dynamics in Colombian economy.
RiSE-group enters the top 25% of RePEc's ranking of research in Economics and related fields in Colombia
Professor Ye is assistant professor at the School of Earth, Environment, and Society (Bowling Green State University).
Professor Sastré is the Director of Spatial-SEALab and full time Professor and Researcher of Spatial Econometrics at the Centro de Investigaciones Socioeconómicas, CISE, Universidad Autónoma de Coahuila.
The subdirector of prospective planning of Medellin City mentioned RiSE group in Tecnova
