Phd in INFRASTRUCTURES AND TRANSPORT

Thesis title: Towards Sustainable and Efficient Last-Mile Logistics: From Routing Algorithms to Crowdshipping Solutions

Urban logistics faces challenges as e-commerce growth exacerbates the complexities of last-mile logistics (LML). This thesis addresses these challenges by exploring innovative, sustainable solutions aimed at enhancing operational efficiency and environmental sustainability within urban freight systems. Structured around three core pillars—operational cost and emissions reduction, the calibration of open-source data for improved routing accuracy, and the integration of crowdshipping—the research leverages data analytics and a series of urban case studies to propose transformative approaches for modern logistics. A major focus is the development and necessity of a logistics platform specifically designed for logistics companies, particularly small to medium enterprises that are integral to the supply chain but often lack the resources to innovate independently. This platform facilitates reductions in operational costs and emissions through optimized route planning and delivery scheduling, leveraging both proprietary and open-source data sets. The calibration of open-source urban network data, primarily through OpenStreetMap, is detailed, showing how enhanced data accuracy significantly benefits urban navigation and operational adaptability. Additionally, the feasibility of crowdshipping as an integrated solution within Rome’s existing logistics framework is examined. This innovative model not only supports existing urban infrastructure but also promotes environmental sustainability by reducing CO2 emissions through optimized delivery routes that align with natural commuter flows. The thesis concludes that developing robust, flexible logistics platforms and adopting crowdshipping can significantly enhance the efficiency and sustainability of urban logistics networks. Additionally, by analyzing various operational scenarios through the logistics platform and employing calibration techniques for open-source data, we can further optimize the accuracy and adaptability of these systems, thus improving the overall effectiveness of urban logistics solutions. These findings are potentially important for logistics companies aiming to navigate the increasing demands of urban supply chains effectively. Future research should focus on extending these methodologies to a wider range of urban contexts, evaluating the scalability of these solutions, and further refining the integration of various supply chain approaches to enhance the adaptability and resilience of urban logistics systems.