It is important to establish appropriate performance indicators so that decision-makers can better determine the best alternatives for sustainable urban freight distribution systems. This literature about urban logistics and routing problems is structured and analyzed through a systematic literature review of a total of 201 papers from 2002 to 2023. Three main axes were considered: problem modeling and solution approaches, multimodal transportation, and indicators to assess the performance and sustainability of the distribution networks. There is a growing trend of research on this topic. Indeed, the paper highlighted the academic interest in the analysis of case studies to test the scenarios and network configurations and proposed solution approaches, as well as the adoption of greener transportation modes. To the best of our knowledge, no previous studies have analyzed the literature from the thematic lines proposed in this review, especially those that refer to performance indicators to assess both the freight distribution networks and the transportation modes considered. Advancing stochastic modeling, expanding case studies to underrepresented regions, integrating AI-driven multimodal logistics, and developing social impact indicators are key research directions to enhance the sustainability and efficiency of urban logistics. This review provides a structured foundation for future research by identifying gaps in the literature and offering a thematic roadmap to advance the study and implement sustainable urban logistics solutions. In addition, its findings can assist decision-makers and logistics planners in evaluating current practices, identifying opportunities for improvement, and supporting the development of more sustainable and efficient distribution strategies.


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    Title :

    Trends and Advances in Urban Logistics Research: A Systematic Literature Review




    Publication date :

    2025




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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