10h30 - 10h55
Home healthcare staffing and scheduling
We present a two-stage stochastic programming model for caregiver staffing and scheduling in home healthcare. Results on real-world instances show that when compared with a deterministic model, the two-stage model leads to significant cost savings, as staff dimensioning and staff scheduling decisions are more robust to accommodate changes in demand.
10h55 - 11h20
Stochastic tabu search for scheduling
In stochastic combinatorial optimization problems, the time for computation often represents a constraint. The study addresses a scheduling problem from the healthcare sector with a Tabu Search algorithm. To reduce the simulation effort during the evaluation of the neighborhood, different procedures are applied with a focus on Ranking and Selection.
11h20 - 11h45
Healthcare staff dimensioning and scheduling in a telemedicine context
This project aims to build a decision-support tool to staff dimensioning and scheduling in a telemedicine context. First, historical demand information and the interactions between the medical team and patients are analyzed to create a workload forecasting model. Then, a mathematical programming model is developed to decide the staffing level and to produce schedules for the healthcare team.
11h45 - 12h10
Productivity-driven physician scheduling in emergency departments
Optimal scheduling of emergency physicians is key to respond to the problem of overcrowding of emergency departments. Despite most papers in the literature, we propose a mathematical model that considers each individual productivity to align offer (that depends on each physician) and demand (number of patients). First, historical data from patient demand is analyzed to create a productivity index. Then this index is incorporated into the mathematical model to show how to better organize physician scheduling to meet patient demand.