4 présentations

• 
  10h30 - 10h55

  Home healthcare staffing and scheduling

  • Maria-Isabel Restrepo-Ruiz, prés., Polytechnique Montréal
  • Louis-Martin Rousseau, Polytechnique Montréal

  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

  • Marco Di Candido, prés., Polytechnic University of Milan

  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

  • Nicolas Boez, prés., Polytechnique Montréal
  • Maria-Isabel Restrepo-Ruiz, Polytechnique Montréal
  • Nadia Lahrichi, Polytechnique Montréal
  • Louis-Martin Rousseau, Polytechnique Montréal

  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

  • Fanny Camiat, prés., Polytechnique Montréal
  • Maria-Isabel Restrepo-Ruiz, Polytechnique Montréal
  • Nadia Lahrichi, Polytechnique Montréal
  • Louis-Martin Rousseau, Polytechnique Montréal

  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.