GPS-Enabled Vendor to Rider Assignment for Urban last Mile Logistics Optimization

Abstract

The rapid growth of urbanization and e-commerce has heightened the demand for
efficient last-mile delivery solutions in urban logistics. This project addresses the
inefficiencies in traditional systems by developing a GPS-enabled vendor-to-rider
assignment system tailored for urban last-mile logistics optimization. Leveraging
real-time GPS data, the proposed system dynamically assigns delivery tasks based
on proximity, traffic conditions, and order priorities, significantly improving
delivery efficiency and customer satisfaction. Key features include real-time
tracking, interactive mapping, dynamic route optimization, and integrated
communication tools for seamless vendor-rider interactions. Using an agile
development methodology, the system architecture incorporates scalable micro
services, cross-platform mobile applications, and data-driven algorithms for
optimal performance. Preliminary evaluations reveal an 18% reduction in delivery
times and a 99% reliability rate for notifications, validating the system's capability
to enhance logistics operations. This research contributes to advancing urban
logistics by addressing critical challenges in delivery coordination, paving the way
for future enhancements through predictive analytics and AI-driven optimization.