genetic algorithm for patients scheduling in emergency department: a case study

Emergency departments (eds) in hospitals typically aim to deliver accurate and rapid treatment to patients. the scheduling of patients in eds is a challenging task that depends not only on the triage process but also on the availability of both human (staff) and material resources. in this paper, a real case study is conducted to tackle the issues coming from crowding and long waiting times for patients processing at the largest hospital in the region of sfax (tunisia). an integer programming formulation is proposed to minimize total patient waiting times (pwt) in eds subject to procedural and staff availability constraints. due to the large scale of the treated problem, a genetic algorithm (ga) is developed as a solution method. the efficiency of the presented approach is evaluated based on diverse sets of theoretically and randomly generated instances in a first way and on the actual data obtained from the real case study hospital in a second way. results show significant improvements compared to the first come first served (fcfs) real case study’s rule. the decrease in patient waiting time ranges between 18.84 % to 27.45%.