We further investigated this by plotting all 20 repeated runs of qNParEGO and MO-E-EQI, see Figure . It is notable that the solutions of qNParEGO tend to aggregate at the bottom right corner (Figure ), while MO-E-EQI suggests more diverse results for both objectives (Figure ). Due to the properties of the current reaction simulator, where the true Pareto front is quite perpendicular, this means that if there are points occupied at the right bottom corner (at maximum STY) and closed to the true Pareto front, HV distance will decrease quickly. Even though MO-E-EQI adds more points for the other objective, this does not show a significant decrease of HV distance as qNParEGO does. Therefore, although HV can describe how close the solutions are to the real Pareto front, it cannot describe how spread the solutions are. However, in real applications, the structure of the Pareto front cannot be known a priori, therefore, algorithms need to be evaluated from different perspectives and this will be further explained in the following sections.