BeschreibungHealthcare services, especially home healthcare services (HHC), are of great significance in today's western world, where the average age is steadily increasing. HHC services are particularly popular, since patients prefer being nursed at home than at retirement homes. However, finding a good schedule is challenging: 1. Nurses need to arrive at the patients' homes in certain time windows, 2. Each service requires a qualification that the nurse must hold (e.g. a nurse for cleaning may not perform a medical service) 3. The schedule should meet preferences of patients, nurses and employer. 4. All legal and contractual issues (such as sufficient resting periods) should be satisfied. We consider a real-world setting, where the objective is to find a schedule with minimal travel time (to reduce operational costs), such that all patients are assigned a nurse, satisfying as many side constraints from the above as possible. Our goal is to construct a flexible framework that generates efficient nurse schedules for different home care companies. Real-world HHC problems are challenging for many reasons. First, the HHC problem constitutes a combination of two NP-hard problems: vehicle routing with time windows and nurse rostering. Therefore, we need to employ a heuristic approach since exact solving methods can typically only tackle small instances. Second, real-world instances include many side constraints that vary greatly between different service providers (e.g. different nurse contracts). Hence we require a flexible solving architecture, where constraints can be easily added/removed. Third, to provide accurate schedules, it is crucial to use accurate travel time estimations, regarding different modes of transport. Therefore,we include travel time estimations from a large set of historical data for different transport modes (car, public transport, bike, foot) into our system.
|12 Mai 2011 → 14 Mai 2011
|2nd Alpen Adria Workshop on Optimization
- Ehemaliges Research Field - Mobility Systems