Published Paper Details:

The truck booking system in urban logistics play a crucial role in facilitating efficient goods and services movement. The current manual truck selection process has been burdened by time-consuming procedures and errors, leading to customer dissatisfaction due to mismatched truck-cargo combinations. To overcome these challenges, the "Study of Intelligent Truck Booking Recommendation System" delves into the application of advanced algorithms and data-driven insights, aiming to automate and enhance the selection process. Through a comprehensive survey, historical data, customer feedback, truck prices, and freight rates are analyzed to generate accurate and efficient truck recommendations. The study emphasizes sophisticated machine learning algorithms, thorough past record analysis, incorporation of customer feedback, cost optimization, cargo weight consideration, and user-based recommendations for new customers. The findings show promising results in terms of increased efficiency, cost savings, improved customer experience, data-driven decision-making, and scalability, offering transformative benefits for the urban logistics industry.