TY - JOUR ID - 2914 TI - Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study JO - International Journal of Supply and Operations Management JA - IJSOM LA - en SN - 23831359 AU - Jlassi, Jih猫ne AU - Rekik, Ines AU - Elloumi, Sonda AU - Chabchoub, Habib AD - Route Tunis km 10 AD - ISGIS AD - OLID AD - Al Ain University of Science and Technology Y1 - 2023 PY - 2023 VL - 10 IS - 4 SP - 439 EP - 455 KW - Emergency department KW - Patient Waiting Time KW - Patients Scheduling Problem KW - Genetic Algorithm KW - Case Study DO - 10.22034/ijsom.2023.109945.2766 N2 - 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鈥檚 rule. The decrease in patient waiting time ranges between 18.84 % to 27.45%. UR - http://www.ijsom.com/article_2914.html L1 - http://www.ijsom.com/article_2914_d7bd0820a1898fc73482fb3c277775e8.pdf ER -