Terminal operations consist of the motion of full and empty containers between gateways of thernterminals. In this study the problem focus on loading/unloading operations, driverâ€Ÿs waits due torncustoms clearance and other related processes, lack of technical and technological capacity as arnresult loading/unloading operation becomes tardy and causes labor productivity issues,rnoperatorsâ€Ÿ schedule reliability, and various types of equipment utilization decreases the servicernquality and customer satisfaction. rnThe objective of this paper is to identify the current practices and challenges in the warehousernand to set strategies that optimize and improve warehouse operation performance using ARENArnsimulation. The scope of study is focusing on Kality dry port and terminal at Addis Ababa. rnThe procedures include data gathering, model building, simulation, verification, and validationrnand performance analysis. Then the model is simulated using the actual container and warehousernoperation through collecting data which include the daily empty and full in/out containers,rnservice requirement, parameters, operation schedule and port machine breakdown. The output ofrnthe simulation is generated in a form of report. The results show that the percentage error ofrnARENA model is less than 5% as targeted. rnThis research propose three major decision options(scenarios) to improve the system. Thernfirst scenario is changing level of resource at port operation with higher number of waiting. Thernsecond one is avoiding unnecessary duplication resource from processes with low capacity rnutilization to increase the operation output and capacity utilization. Lastly, third scenariornfocused on merge similar operations through reduced resource to 12 from existing 25 andrnpercentage of productivity per operator for full-in: full-out operation and empty-in: empty- outrnoperation is improved to 84.72% and 63.19% from existing 48.36% and 41.11% respectively. rnFinally, the research has recommended the enterprise use from creating differentrnopportunities and overcome the challenges as well as the optimization of the dry portrnwarehouse operation system.