To compare the performances of MOBO algorithms, several metrics have been proposed in the literature to evaluate how close the solutions are to the Pareto front and how evenly the solutions are distributed along the frontier, as shown in Figure and Figure . In addition, the number of solutions on the Pareto front is also important because it provides more choices to decision-makers. In this study, MOBO algorithms were evaluated using hypervolume-based metric, coverage metric and number of Pareto optimal solutions for comparisons. The hypervolume-based (HV) metric is widely recognized as a unary value which is able to measure the closeness of the solutions to the optimal set . The hypervolume metric calculates the volume of the objective space covered by members of an obtained Pareto set P bounded by a reference point R (see Figure ):