To conduct the experiment for the GI/M/1/N queueing model, follow these detailed steps:

1. Set Simulation Parameters:

   • Select the Arrival Time Distribution: Choose the appropriate distribution for the inter-arrival times, which could be general (GI), meaning it does not follow a specific exponential distribution.
   • Set the Mean Arrival Rate: Input the average rate at which customers arrive at the system.
   • Set the Mean Service Rate: Input the average rate at which the single server can process customers.
   • Set the Maximum Number of Customers: Define the system's capacity, which is the maximum number of customers that can be present in the system (both in service and in the queue) at any given time.

2. Ensure Steady-State Conditions: -Ensure that the mean arrival rate is less than the mean service rate. This is crucial for the system to reach a steady state, where the queue does not grow indefinitely, and the system can operate in equilibrium over time.

3. Start the Experiment:

   • Initiate the Simulation: Click the 'Start' button to begin the simulation. The system will start processing customers based on the parameters you have set, simulating the arrivals, services, and departures.

4. Stop the Experiment and View Results:

   • Halt the Simulation: After allowing the simulation to run for a sufficient period to gather data, click the 'Stop' button.
   • View Results: Examine the steady-state results provided by the simulation. These results will be available both numerically and graphically, showing metrics such as the average number of customers in the system, blocking probability, average waiting time, and server utilization.

5. Compare Theoretical and Experimental Results:

   • Analyze the Data: Compare the numerical and graphical results obtained from the simulation with the theoretical predictions of the GI/M/1/N model. This comparison helps validate the theoretical model and provides insights into the system's performance under different conditions.