Optimizing supermarket checkout using an open queuing network model with rule based allocation

This paper presents Open Jackson queuing network model that optimizes supermarket checkout operations through rule-based dynamic lane allocation. Customers enter the system randomly, are routed to suitable checkout lanes (self-checkout, express, standard, and special assistance), and exit after service. Lane selection is governed by predefined logic based on basket size, queue length, and customer profile. The model is simulated using discrete event simulation, with performance evaluated through waiting time, lane utilization, and queue length. Compared to static selection, rule-based routing significantly reduces waiting time and improves resource utilization, offering a practical, cost-effective alternative to AI-driven solutions.