Optimal route planning using computer simulation in the context of distributor-to-consumer supply network

Effective route planning for distribution centers is a multifaceted challenge crucial to business success, as it directly impacts time and cost savings while enhancing overall delivery efficiency. Oversight of proper planning can lead to problems and inefficiencies in the distribution process. Hence, this work undertakes a comparative experiment of two delivery strategies in a distributor-to-consumer supply network. While the first strategy investigates the delivery process by zip area, the second strategy considers the clustering of the areas for more streamlined delivery fulfillment. The effectiveness of the delivery process is gauged based on a set of metrics, including total distance traveled, average delivery time, missed target deliveries, and resource utilization. The study specifically addresses five distribution centers in the El Paso, Texas, USA, area and the delivery addresses across various zip codes in El Paso. The delivery network was simulated using the AnyLogic software, with results analyzed on both daily and weekly timelines. Simulation data were systematically logged into the AnyLogic database for subsequent analysis. In doing so, this paper presents a comprehensive analysis derived from observed data, offering a comparative assessment of the two delivery strategies. The findings provide a quantitative evaluation of the effectiveness of route planning within diverse scenarios in end-user supply networks.