Research in Humanitarian Operations (HO) has attracted the attention of academics and practitioners by applying analytical tools to improve response to beneficiaries. Different studies suggest that the integration of traditional practices and theories of logistics and operations management (OM) in the complex context of disasters would benefit the humanitarian supply chain. One of the most recognised techniques in OM is simulation, being System Dynamics (SD) a method capable of model simplified representations of realities and gain valuable insights into situations of dynamic complexity. In this context, this thesis aims to analyse the complexity of HO through SD. The thesis presents a systematic literature review (SLR) to identify the state of the art of the subject, delivering a taxonomy, a framework, and a research agenda. Then, two complex and dynamic operations are modelled through SD. The first operation involves collecting and distributing donations to the vulnerable population from Rio de Janeiro, Brazil, amid the COVID-19 pandemic. As a result, we demonstrated that: (i) increasing access to cleaning products in communities can significantly reduce COVID-19 transmission; (ii) food donations can increase the population s affordability; (iii) accessibility increases by 20 percent in vouchers/cash donations compared to all in-kind donations. The second one is the Brazilian operation to receive, shelter, and internalise Venezuelans. Since the flow of Venezuelans to Brazil has grown and, the pandemic aftermath presents itself as a concern for the operation capacity, Operation Welcome is modelled to understand the bottlenecks for its scalability. As a result, we demonstrate that: (i) the internalisation process is a bottleneck as, in addition to logistics, it is necessary the socio-economical insertion (through job vacancies, for example); (ii) shelters capacity is an operation bottleneck, as it defines a queue of needing assistance Venezuelans waiting to be sheltered.