Humanitarian Operations (HO) encompasses disaster relief activities. The ability to conduct these operations efficiently and effectively is a critical element of a disaster response process. Since disasters are complex, severe, and dynamic events, with limited human and material resources and a high level of information uncertainty, the ability to manage operations (Operation Management - OM) is essential. Research in HO and disasters operation management (DOM) has attracted academics and professionals attention by covering the study of different analytical tools aimed at improving the response to beneficiaries. Different studies suggest that the insertion of traditional commercial supply chain practices and theories - including simulation, optimization, probability, and statistics - in the context of disasters would benefit the effective humanitarian supply chain. One of the most commonly recognized techniques in OM and DOM is the simulation. In particular, System Dynamics (SD) is the most popular simulation technique in the context of disaster management. SD is used to study complex problems with computational simulations, qualitatively and quantitatively, solving issues of multivariate, high-order, and multi-feedback nonlinear systems. The method provides a set of tools, such as causal mapping and simulation modeling, and evaluates the short and long-term results of decisions. In this context, the present thesis aims to propose SD models in HO and DOM. For this, the thesis presents a systematic literature review (RSL) to identify the state of the art regarding the subject and the literature s GAPs. Then, two case studies are developed, demonstrating the application of SD in two different humanitarian contexts.