Understanding Population Dynamics in Multi- and Many-Objective Evolutionary Algorithms for High-Resolution Approximations

Figure 1

Resolution of the approximation at the end of the run , that is, ratio of the accumulated number of Pareto optimal solutions found to the size of the POS. Population sizes 50, 100, and 200 for 3, 4, 5, and 6 objectives. Algorithms , , , NSGA-II (N), and MOEA/D (M). (a) M = 3 objectives, (b) M = 4 objectives, (c) M = 5 objectives, and (d) M = 6 objectives.

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