AI-Driven Optimization for Freight and Logistics Management Using Predictive Analytics
Angelina Royappa, K. Venkatesh, N. Purushothaman, A. Moorthy, P. Solainayagi
Abstract
This study focuses on the application of AI in the freight and logistics management with perspective on predictive analysis for improvement of efficiency and sustainability. The study highlights deserve performance improvements such as; Nonetheless, the study applies machine learning models in demand forecasting, route optimization, load management, and inventory management, results into; Credible evidence also supports these facts and statistics; for instance, a real-world case study proved that it is possible to reduce the operational cost by 17% and improve the customer satisfaction level by 22%. Though there are issues regarding the implementation cost and maintaining data privacy this research showcases the possibilities of using AI in logistics leading to enhanced supply chain sustainability. The knowledge generated in the course of the study is beneficial to professional end-users who plan to utilise AI for business advantage and survival.