Scheduling mobile dental clinics: A heuristic approach considering fairness among school districts

Abstract

Mobile dental clinics (MDCs) are suitable solutions for servicing people living in rural and urban areas that require dental healthcare. MDCs can provide dental care to the most vulnerable high-school students. However, scheduling MDCs to visit patients is critical to developing efficient dental programs. Here, we study a mobile dental clinic scheduling problem that arises from the real-life logistics management challenge faced by a school-based mobile dental care program in Southern Chile. This problem involves scheduling MDCs to treat high-school students at public schools while considering a fairness constraint among districts. Schools are circumscribed into districts, and by program regulations, at least 50% of the students in each district must receive dental care during the first semester. Fairness prevents some districts from waiting more time to receive dental care than others. We model the problem as a parallel machine scheduling problem with sequence-dependent setup costs and batch due dates and propose a mathematical model and a genetic algorithm-based solution to solve the problem. Our computational results demonstrate the effectiveness of our approaches in obtaining near-optimal solutions. Finally, dental program managers can use the methodologies presented in this work to schedule mobile dental clinics and improve their operations.