**4. Experimental Results**

As noted in previous sections, for the experimental study we considered the bi-objective KNP and TSP formulations. Moreover, we have described the set of instances that could be used in the context of these formulations. Regarding the type of approaches to apply, as mentioned previously, we are interested in evaluating the possibilities offered by a multi-objective optimization mechanism where we analyze, from the resulting Pareto front, the end points in each objective independently. The optimization approaches compared herein consist of three MOEAs (NSGA-II, MOEA/D, and SMS-EMOA) and two single-objective algorithms (gGA and eES). Note that, initially, we checked the behavior of four single-objective approaches, but two of them (ssGA and neES) were discarded for the exhaustive study presented here. This is because the results output by these algorithms were not at all competitive when compared to the single-objective algorithms finally selected for our comparisons (gGA and eES).
