Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro

Abstract

Paper aims: This work aims at proposing a mathematical model for allocation of oncological treatment units of SUS. Originality: A model of the same architecture was not found in the literature for the delimited problem. Research method: The mathematical models of location in the literature were reviewed and based the choice by the two-level hierarchical pq-median model with additional constraints of maximum distance and vertices eligibility, which was implemented in the CPLEX optimization software. Main findings: Satisfactory results with homogeneous networks, centralized facilities in their service area and shorter distance traveled by users indicate the efficiency of the model in determining the optimum location given the number of facilities to be allocated. Implications for theory and practice: The model proved to be an efficient tool to assist health managers in their decision-making about the network of facilities, not just oncological, but of any nature and many others public sectors.

An efficient and robust hybrid metaheuristic method to solve a hierarchical bi‐level protection‐interdiction problem on real healthcare system

“…The queuing system was integrated to deal with stochastic demand, service time, and a service level evaluation. Vieira et al 32 proposed two hierarchical facility location models (HFLM) for allocation of oncological treatment units of the unified health system. The first model optimized the effective utilization of the state's financial resources, to minimize costs to public coffers for ensuring coverage of all demand, while the second one optimized the population's access to the service, developing quality by minimizing the distance traveled by patients to the service points.…”

Solving a University Admission Exam Location Problem: An Application in Brazil

“…There is a large production of works related to the facility location subject with different approaches, presenting a wide range of mathematical models, heuristic algorithms, and theoretical analyses (Klose andDrexl 2005, Owen andDaskin 1998). It is a very relevant topic when it comes to supply chain management, as shown by the in-depth analysis of Melo et al (2009), but also especially in areas such as health care (Burkey et al 2012, Huang et al 2010, Vieira et al 2019) and humanitarian logistics (Cotes and Cantillo 2019, Lin et al 2012, Murali et al 2012. Moreover, like the approach presented in this work, it is widespread in facility location problems the use of geographic information systems, as in Matisziw and Murray (2009), Shen (2005).…”