Resumo:
Disruptive events have the potential to deeply impact how companies manage and operate their supply chains. These events can be triggered by a variety of factors such as natural disasters, pandemics, regulatory changes, technological innovations, or geopolitical disruptions. Their occurrence is inevitable, and it is essential for companies to be prepared to face them. Of particular interest for this work is e-commerce and its impact on Urban Freight Transport (UFT) during and after disruptive events. In this context, the use of decision support tools can aid in seeking solutions to mitigate the impacts of these events, ensuring the resilience of transportation operations even in turbulent times. During a disruptive event, the volume of delivered orders can significantly increase, creating a demand for e-commerce deliveries that exceeds expectations. This directly impacts the operation of carriers in urban environments, facing a significant increase in delivery demand. The aim of this thesis is to present DISRUPSIM: a decision support tool for urban freight transport of e-commerce during disruptive events. The proposed tool operates through a hybrid simulation model, combining Discrete Event Simulation with Agent-Based Simulation, enabling the evaluation of City logistics initiatives for UFT of e-commerce during disruptive events. In this thesis, its application is demonstrated in a real case: scenarios were developed for comparative analysis and modeling of delivery demand based on data provided by a carrier. Scenario construction aimed to model delivery demand before and after a disruptive event, considering the COVID-19 pandemic period for this purpose. In the application, the use of Delivery Lockers was evaluated as a City logistics initiative to alleviate the impacts on carrier operations. The tool proved to be versatile, easily adoptable by any carrier, simply by adjusting input parameters and location according to the particularities of their local operation. Additionally, other City logistics initiatives for UFT of e-commerce can also be evaluated by adapting modeling processes and model input data, mitigating impacts on e-commerce delivery operations. Through the results generated by this tool, comprehensive analyses can be conducted, including data on distance traveled, total transported distance, cargo volume moved, CO2 emissions, fuel consumption, number of trips made, and vehicle occupancy at the time of departure for deliveries. Furthermore, the tool allows for the evaluation of performance indicators and the energy efficiency of the carrier. In a practical scenario, in the case studied, the tool showed great promise, demonstrating a potential energy savings of up to 60% in terms of orders delivered and volume transported. These results demonstrated the applicability of the tool for decision support and the evaluation of initiatives aimed at UFT during disruptive events, thus aiding in the search for more efficient and sustainable solutions in the transportation of goods in urban areas.