The shape of Pareto fronts in optimization algorithms affects their performance. Regular triangular Pareto fronts are not realistic for real-world problems. Other test problems have inverted triangular Pareto fronts. The shape of Pareto fronts impacts decomposition-based and hypervolume-based algorithms. Hypervolume-based evaluation is challenging for many-objective problems with inverted triangular Pareto fronts.