OPTIMIZING LAST-MILE DELIVERY IN RETAIL THROUGH AI-POWERED ROUTING AND SCHEDULING
Keywords:
Last-mile Delivery, Retail Logistics, AI Algorithms, Routing Optimization, Scheduling Algorithms, Predictive Analytics, Real-time Decision-making, Machine Learning, Autonomous Vehicles, Blockchain Transparency, Supply Chain ManagementAbstract
Last-mile delivery, the final stage of the delivery process from a distribution center to the customer's doorstep, is a critical component of the retail supply chain. The purpose of this study is to examine how AI technologies can enhance efficiency, reduce costs, and elevate the customer experience in this crucial phase of delivery. This research paper explores the integration of AI-powered solutions in last-mile delivery operations within the retail sector. Through a comprehensive analysis of challenges, opportunities, and case studies, it investigates the impact of AI technologies on enhancing efficiency, reducing costs, and improving the customer experience in the final stage of the delivery process. The paper discusses algorithmic approaches to routing and scheduling, evaluates the effectiveness of AI in achieving efficiency gains and cost savings, addresses practical considerations and implementation challenges, and explores future directions and opportunities for further enhancement. By providing insights and strategies for retailers, this paper serves as a roadmap for leveraging AI to optimize last-mile delivery operations and drive innovation in the retail logistics landscape.
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