Operating rooms scheduling using Variable Neighborhood Search meta-heuristic

Healthcare systems around the world are faced with rising costs, increasingly complex illnesses and declining reimbursements. In this context, problems related to health optimization are complex, because they concern the fabrication of schedules that absorb the disturbances occurring in the future. The operating room is a complex environment, at risk for the safety of the patient, and which involves many stakeholders. Its organization must be based on a reflection around the management of flows to contribute to the improvement of the patient's journey. In this paper, we propose a smart operating rooms scheduling using Variable Neighborhood Search (VNS) meta-heuristic. According to the literature review, VNS meta-heuristic approach still underused to resolve the cited issue. In this work, we have developed two VNS basic schemes of (Variable Neighborhood Descent (VND) and General VNS (GVNS)) in order to show their efficiency to meet operating rooms planning and scheduling problem challenges.