Oussama Barakat

Impact analysis of workload balancing on the home health care routing and scheduling problem

Home health care optimization is a trending research topic in the recent years since the demand for home health care rises. An important aspect of the problem is the workload balancing among caregivers that must be fair. However, the workload can be defined differently since the work of a caregiver can be composed of different activities: traveling time, time spent providing cares and idle time. Moreover, the home health care routing and scheduling problem with workload balancing is a multi-objective problem leading the working time balancing to increase the value of the total working time and soft patients time window and shared visits non-satisfaction. In order to obtain a good balance between all objectives, we perform an impact analysis of the caregivers activities balancing in order to identify the appropriate activities to balance instead of the whole working time. A mixed-integer programming representation of the problem is proposed and a memetic algorithm is used to evaluate the model on literature instances. An analysis of the results reveals the importance of the choice of the balanced activities in order to obtain an acceptable balance between workload balancing and the other objectives according to decision-makers strategy.

Particle Swarm Optimization for Operating Theater Scheduling Considering Medical Devices Sterilization

The operating theater scheduling problem is one of the main hospital sector issues of today’s world. Indeed, numerous papers dealing with this subject may be found in the literature. However, the synchronization between the pharmacy (providing the surgical devices and medicines) and the operating theater is rarely studied. Nevertheless, the importance of the pharmacy keeps growing because of the creation of numerous hospital groups composed of several hospital complexes sharing a central pharmacy. In this paper, we focus on the sterilization cycle of the surgical devices to provide operating theater scheduling methods taking into account pharmacy issues. We present exact methods with a mixed integer linear programming model to determine optimal schedules as well as approximate solutions with a particle swarm optimization based method to solve the most complex cases. These modelings provide interesting schedules using few quantities of surgical devices boxes even when considering many procedures. With this study we hope to lay the foundations of a transverse logistics unifying the operating theater and the pharmacy in a multi-site context.