A data-driven optimization framework for routing mobile medical facilities
Yücel, Eda; Salman, F. Sibel; Bozkaya, Burçin; Gökalp, Cemre
Why this matters
Better routing can extend a mobile program's reach without adding vehicles or staff. The paper formulates joint stop selection and routing for mobile medical vehicles over a repeating multi-day schedule as a team orienteering problem, maximizing the population covered while holding down travel distance.
Abstract
We study the delivery of mobile medical services and in particular, the optimization of the joint stop location selection and routing of the mobile vehicles over a repetitive schedule consisting of multiple days. Considering the problem from the perspective of a mobile service provider company, we aim to provide the most revenue to the company by bringing the services closer to potential customers. Each customer location is associated with a score, which can be fully or partially covered based on the proximity of the mobile facility during the planning horizon. The problem is a variant of the team orienteering problem with prizes coming from covered scores. In addition to maximizing total covered score, a secondary criterion involves minimizing total travel distance/cost. We propose a data-driven optimization approach for this problem in which data analyses feed a mathematical programming model.