How to Cite: Mittal, H., & Sharma, N. (2022). A simulation-based approach for minimizing waiting time in AIIMS, Delhi using Queuing model. International Journal of Health Sciences, 6(S5), 7037–7054. https://doi.org/10.53730/ijhs.v6nS5.10227 International Journal of Health Sciences ISSN 2550-6978 E-ISSN 2550-696X © 2022. Manuscript submitted: 9 April 2022, Manuscript revised: 18 June 2022, Accepted for publication: 27 July 2022 7037 A simulation-based approach for minimizing waiting time in AIIMS, Delhi using Queuing model Himanshu Mittal School of Engineering and Sciences, GD Goenka University, Gurugram, Haryana, India Email: himanshu1000mittal@gmail.com Naresh Sharma School of Engineering and Sciences, GD Goenka University, Gurugram, Haryana, India Corresponding author email: naresh.sharma2006@gmail.com Abstract---The government hospitals in India influenced by multiple factors causing longer waiting time of patients in comparison to private hospitals, which worsen the threat to healthcare facilities. The optimization of available resources considering the arrival rate of patients and the availability of facilities for the minimization of queuing is the utmost requirement. The current study has been carried out within the outpatient's department to minimize queue length of one of the largest and busiest hospital, AIIMS in Delhi, represent a struggling health care delivery system with high waiting times of patients. The primary queuing data was collected for total samples of 1200 patients during the four-week study period (1 st July to 30 th July 2020), (Monday-Friday) and working hours of general OPD (08:30 am to 01:00 pm). The detailed queuing secondary data was collected from AIIMS for three years (1 st January 2015 to 31 st July 2017). Data has been analyzed by queuing models, M/M/1: Poisson- exponential, single server model-infinite population and up to M/M/8: Poisson-exponential, multiple server model-infinite populations. Keywords---Queuing model, Optimization of Queues, AIIMS, single server model and multiple server model. 1 Introduction A significant criterion for efficiency measurement within the service industry is the waiting time (Tadj, 1996; Sharma et. al. 2010, 2011). The issue of waiting times of patients and queue length assessment has been widely researched in