Innovative location-routing optimization using k-mean clustering algorithm and MTZ-TSP model

Inspired by the challenges of last-mile delivery, this project presents an innovative location–routing optimization framework that integrates the k-means clustering algorithm with the MTZ-TSP model. In the first stage, demand points are clustered, and their centroids are identified as strategic hubs. In the second stage, optimal routes between these hubs are determined to minimize travel distance, shorten delivery time, and enhance operational efficiency. The framework’s performance was evaluated using three datasets. Although not applied to a real-world case, it shows strong commercial potential in sectors such as e-commerce, courier services, waste collection, public transport planning, and emergency response. This work also supports SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities) by enabling smarter resource use, lowering environmental impact, and enhancing service delivery.