Last-Mile Delivery Routing Using Ant Colony Optimization and Google Maps API
DOI:
https://doi.org/10.47065/bulletincsr.v6i6.1272Keywords:
Last-Mile Delivery; Ant Colony Optimization; Vehicle Routing Problem; Route Optimization; Google Maps Distance MatrixAbstract
The rapid growth of e-commerce has significantly increased the demand for efficient last-mile delivery, making route optimization an essential challenge for logistics providers. Conventional manual route planning often depends on driver experience and may fail to produce efficient delivery sequences, particularly as the number of destinations increases. This study proposes a web-based last-mile delivery routing optimization system that integrates Residential Delivery Clusters, the Google Maps Distance Matrix Application Programming Interface (API), and the Ant Colony Optimization algorithm to generate practical delivery routes based on actual road-network distances. Residential Delivery Clusters group destinations within the same residential area through representative entrance points, enabling the routing model to better reflect real-world delivery environments while reducing route complexity. The proposed system was evaluated using seven real delivery scenarios containing between 5 and 62 delivery locations obtained from an expedition service in Bekasi Regency, Indonesia. Experimental results demonstrate that the proposed approach consistently improved routing performance by reducing total travel distance by 0.07% to 23.91% compared with manually planned routes. Notably, the optimal testing scenario comprising 62 delivery points achieved a substantial travel distance saving of 60.62 km. Furthermore, route planning time was reduced by 60.2% to 89.6% relative to manual planning performed by experienced expedition drivers. These findings indicate that integrating residential delivery clustering with road-network-based optimization can improve routing efficiency and substantially reduce operational planning effort, making the proposed approach suitable for practical implementation in real-world last-mile delivery operations.
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