Healthcare Emergency Department modeling and optimization analysis is one of the tools that havernbeen applied to model and analyze the resource scheduling and performance of a healthcare system.rnThe modeling can be done either by analytical or simulation methods. The major problems of TikurrnAnbessa Specialized Hospital, Emergency Department is overcrowding related with high length ofrnstay, low throughput, high waiting time, low resource utilization, etc. Therefore, the principalrnobjectives of this thesis are to identify the scheduling parameters (key constraints) that affect thernallocation and scheduling of activities; to identify the critical sub activities contributing to lag overallrnprocess and to make a flexible and optimal resource scheduling through modeling. Some papers donernin relation to health care and manufacturing system modeling has been reviewed for this thesis. Patientrnrecords, processing time, etc. primary and secondary data have been collected from the case company,rnthrough direct observation of the process and using stopwatch. Then, the data was analyzed and anrnappropriate model was selected from the available fit of probabilistic distribution. Modeling of the EDrnprocess was made with the help of (i.e. Arenaâ„¢ student version) simulation and modeling software.rnThe model was verified and validated in order to ensure that it behaves the same as the real system andrnfinally analysis of the simulation model was conducted. Based on the analysis the optimized modelrnhas been proposed for implementation. In this thesis, waiting time, length of stay, resource schedulingrnoptimization and flexibility, was used as a measure of the performance of the production line. Afterrnanalyzing the ED process model, a number of problems were identified including; longer queuingrntime, absence of flexible flow lines and lower utilization of resources. Finally, a new model wasrnproposed where the length of stay has decreased by 25.6%, 16.23%, and 27.55% in first triage, frontrnassessment and red/resuscitation processes respectively. This reduction in length of stay increased thernthroughput and reduced the overcrowding of the ED by more than ten percent. The achieved results inrnthe proposed model can be easily adapted after similar studies and the EDs can be improvedrnsignificantly.