An integrated Lexicographic goal programming and dynamic satisfaction function model for effective nurse scheduling

The nurse-scheduling is a common problem in hospitals. The problem requires a timetable considering hospital regulations and nurses' demands and preferences. This study proposes an integrated Lexicographic goal programming and dynamic satisfaction function model for solving nurse-scheduling problems. The proposed model provides the head nurses with a balanced and fair automated schedule. The model considers two aspects related to hospital regulation constraints. First, the dynamic aspect allows the decision-makers to integrate their judgment to the changing circumstances caused by nurse absenteeism. Second, the satisfaction aspect considers the decision maker's preferences in assigning nurses' surplus or shortages to the shifts. The model's primary goal is to give nurses a fair and balanced schedule with an evenly distributed workload. A fair and balanced schedule helps maintain nurses' welfare and provide quality patient service. We present a case study in an intensive care unit to demonstrate the effectiveness of our approach compared to the conventional goal programming method.