Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization

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Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition (2014, background): “2) Performance metrics: As discussed in [49] and [50], no unary performance metric is able to give a comprehensive measure on the performance of an MOEA.”
Performance indicators in multiobjective optimization (2018, background): “Authors of [20] introduce this new metric to correct the defaults of the GD and IGD indicators.”
Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers (2016, unknown): “:3) p [35].”
An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility (2018, background): “, GD [30], IGD [31], HV [32], R2 [33], p [34], pure diversity [35], and IGD-NS [29].”
Modified Distance Calculation in Generational Distance and Inverted Generational Distance (2015, methodology): “It has been repeatedly pointed out in the literature [14], [15], [18], [24], [26] that Pareto non-compliant misleading results can be obtained from some other performance indicators.”
Stable Matching-Based Selection in Evolutionary Multiobjective Optimization (2014, background): “No unary performance metric can give a comprehensive assessment on the performance of a MOEA [29], [30].”