The decision-making process in humanitarian logistics comprises several types of priorities that are sometimes related to life or death situations. In this degree of importance, the objectives to be pursued by decision-makers in the event of a disaster as well as the constraints of the problem must be established to align both with the needs of the victims and with the existing limitations. This study aims at analyzing how conflicting priorities in an uncertainty-filled problem such as a disaster can impact the performance of the solution with respect to its efficiency, effectiveness and equity (3E). The dissertation presents the role of some decision-making trade-offs within disaster preparedness phase. For this, stochastic optimization models are proposed using the concept of 3E-performance and risk sensitivity, through the measure CVaR. Results indicate that the inclusion of risk aversion may lead to a more effective system on average. Another important point is that the cost minimization model including the shortage penalty provided a better performing response than in equity or coverage maximization independently. In addition, budget constraint (efficiency) when poorly dimensioned can make a problem of maximizing coverage (effectiveness) unnecessarily inefficient. It is concluded that the prioritization of the joint maximization of efficiency and effectiveness with restriction of inequity and risk sensitivity makes a model more precise as regards the care of the disaster victims.