A multi-agent system can be helped by a normative system that guides its (autonomous) agents towards an expected behavior. These agents on their side have to reason about the impact of those norms in their personal desires. Considering that agents have limited resources, it is necessary to reason also about available resources and whether they are enough to reach goals generated by norms and desires. The Huggin proposes and implements a deliberation process that uses the concept of mood to reason about norms, desires and resources. The proposed deliberation process is conceived as an optimization problem known as multidimensional knapsack problem with multiple-choice. The computational complexity of this process is NP-complete and thus it can likely be a bottleneck in the agent reasoning cycle. The main goal of this paper is to identify how the desires, norms and resources (input variables) impact in the reasoning cycle execution. Considering the input variables, we empirically measure their impact on the usage percentage of Huginn in the agent overall process time. We conclude in this work that, despite of the process complexity, the impact on the reasoning is acceptable for the usual number of norms, desires and resources of current MAS applications.