Low Cost Automation of Last Mile Delivery

Last-mile delivery remains a significant logistical challenge, requiring cost-effective automation to optimize routes, resource allocation, and package handling. This paper presents a low-cost automation framework for last-mile delivery that integrates a capacitated vehicle routing problem (CVRP) with dynamic pickups, 3D bin packing, and multi-modal optimization. We propose scalable algorithms that leverage computer vision for volume estimation, heuristic-based route planning, and dynamic scheduling to minimize operational costs while maximizing efficiency. Experimental results demonstrate reduced travel distances, improved load utilization, and enhanced delivery reliability. Our approach provides a practical and scalable solution for automating last-mile logistics, ensuring timely and cost-efficient deliveries.