AI Summary & Key Takeaways
AI InsightComputational experiments prove that our approach can findnew potential pharmacy warehouses which cover wider areas than current warehouses to service pharmacies and hospitals in the city.
📌 3 Key Takeaways
Abstract
It is a known fact that basic health care services cannot reach the majority of the population due to poor geographical accessibility. Unless quantitative location-allocation models and geographic information systems(GIS) are used, the final decision may be made on pragmatic considerations which can result far from optimal. In this paper, current and possible (or potential) new locations of pharmacywarehousesinGaziantepareinvestigatedtoprovideoptimal distribution of hospitals and pharmacies. To do so, first of all, geographic informationof10currentand10potentialpharmacywarehouses,231 pharmacies and 29 hospitals are gathered using GIS. Second, a set covering mathematical model is handled to determine coverage capability of current and potential pharmacy warehouses and minimize the number of warehouses to be opened. Finally, P-center and P-median mathematical models are applied to open potential warehouses and to assign pharmacies & hospitals to the opened warehouses so that the total distance and the demand's longest distance to the source are minimized. Developed integer programming (IP) models and GIS software are compared with on a case study. Computational experiments prove that our approach can findnew potential pharmacy warehouses which cover wider areas than current warehouses to service pharmacies and hospitals in the city.