LAUSR

The home health care (HHC) covers a wide range of health care services carried out in patients’ home in case of illness, injury or aging. Each caregiver should as far as possible adhere to the schedule set by the decision maker. However, unforeseen events would sometimes occur and delay the delivery of care services, which will qualify the service as poor or even risky. Deterministic models ignore this uncertainty, which can arise at any time and will therefore lead to non-compliance with the predefined schedule. Furthermore, patients need several care activities per day, and some of them require to be simultaneous by their nature such as dressing, getting out of bed and bathing. In this work, a stochastic programming model with recourse (SPR model) is proposed to deal with the home health care routing and scheduling problem (HHCRSP) where uncertainties in terms of traveling and caring times that may occur as well as synchronization of services are considered. The objective is to minimize the transportation cost and the expected value of recourse, which is estimated using Monte Carlo simulation. The recourse is defined as a penalty cost for patients’ delayed services and a remuneration for caregivers’ extra working time. The deterministic model is solved by CPLEX, the genetic algorithm (GA) and the general variable neighborhood search (GVNS) based heuristics. The SPR model is solved by Monte Carlo simulation embedded into the GA. Computational results highlight the efficiency of GVNS and GA based heuristics and the complexity of the SPR model in terms of CPU running times.