Repensar a logística de última milha: customização de estratégias de entrega integradas para um comércio eletrónico sustentável

From the perspective of e-commerce, urban areas have traditionally been managed as homogeneous zones, without considering the specificities related to demand levels, socio-economic aspects, infrastructure, geography, or environment. The LOG-in project aims to create a tactical-strategic Decision Support System (DSS) for improving the sustainability of last-mile logistics operations, considering the unique features of each urban context and the need to devise customized strategies and policies for both operators and regulators. Therefore, the LOG-in project seeks to foster the advancement of sustainable and resilient last-mile logistics strategies, focusing on environmental preservation and societal well-being while maintaining the operational and economic sustainability of logistics operations. The LOG-in project’s objectives can be summarized in the following three groups of main research questions: i. Which are the last-mile delivery strategies available? What are the primary characteristics of urban areas that significantly impact the effectiveness of those last-mile delivery strategies? How do these contextual factors influence the implementation and outcomes of these strategies in urban environments? ii. How can dynamic systems simulation models and ML techniques be effectively combined to evaluate the impacts of specific delivery strategies within various contextual settings? Which are the most suitable last-mile delivery strategies in each specific urban context and why? iii. How can a human-centered system leveraging generative AI provide key recomendations and insights to operators and regulators involved in last-mile delivery services? Can this system enhance their decision-making process and optimizing delivery operations? Due the multidimensionality of the problem, to achieve the objectives and respond to the research inquiries, the project will combine different methods such as geographic analysis, dynamic systems simulation, ML and AI. Although the analysis will be initially focused on individual city sectors, a comprehensive assessment of last-mile operations across an entire city or metropolitan area will also be considered. The insights and models generated will be utilized to develop an integrated Decision Support System aimed at enhancing decision-making processes and facilitating the implementation of delivery solutions that cater to the specific needs and constraints of various geographical contexts. The system will incorporate multiple factors such as environmental impact, social considerations, and economic feasibility to offer holistic solutions tackling the challenges encountered by logistics operators and regulators in optimizing delivery strategies. Synergies with past and current projects will be established to accelerate and improve some steps of the project.