Bank Queueing Theory Simulation with MATLAB Implementation

We can implement computer simulation of queueing theory using MATLAB. Queueing theory is a mathematical discipline that studies waiting lines and their applications, which can be effectively applied to scenarios like banking systems. In queueing theory simulations, we typically utilize random numbers to model customer arrival times and service processing durations. This approach allows us to evaluate system performance metrics and determine optimization strategies for improving service efficiency.

In our MATLAB implementation, we employ random number generators (such as rand() or randn() functions) to simulate stochastic arrival patterns and service times. Key components include:

1. Arrival Process Simulation: Using exponential distribution for inter-arrival times with lambda parameter representing arrival rate 2. Service Time Modeling: Implementing service duration distributions (exponential, normal, or uniform) based on system characteristics 3. Queue Management: Coding FIFO (First-In-First-Out) logic with queue data structures 4. Performance Metrics: Calculating average waiting time, queue length, and system utilization through statistical analysis

The simulation framework involves initializing system parameters, running discrete-event simulation loops, and collecting performance data for analysis. This MATLAB implementation provides a practical tool for understanding queueing system dynamics and optimizing service configurations in banking environments.