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Integrating smart technologies into freight operations is essential for achieving efficiency, sustainability, and cost-effectiveness in modern logistics. This research presents a novel smart freight platform to optimize matching and routing in freight logistics. The platform incorporates sequential matching and a dynamic bidding mechanism, including Pre-filter matching, Main matching, and Non-Contracted Shippers (NCS) matching models. It utilizes the Vehicle Routing Problem with Time Windows (VRPTW) model to align delivery schedules with shippers’ time windows. The proposed platform reduces resource consumption by minimizing empty truck routes through NCS alignment with en-route trucks. In particular, empty truck routes were reduced by %39, while gas emissions decreased by over nine tons daily. Therefore, the proposed platform not only improves freight efficiency but also contributes to environmental sustainability. • A sequential matching and routing framework is developed for freight logistics. • Matching includes three stages: Pre-filter, Main, and NCS-specific consolidation. • A VRPTW model is integrated to optimize route planning and delivery scheduling. • The approach reduces empty truck trips by 39% and cuts CO2 emissions by 9 tons/day. • H3 hexagonal grids improve spatial accuracy over traditional radius-based methods.
Sami et al. (Thu,) studied this question.