Multio-bjective ranking and selection based on hypervolume

In this paper, we propose a myopic ranking and selection procedures for the multi-objective case. Whereas most publications for multi-objective problems aim at maximizing the probability of correctly selecting all Pareto optimal solutions, we suggest minimizing the difference in hypervolume between the observed means of the perceived Pareto front and the true Pareto front as a new performance measure. We argue that this hypervolume difference is often more relevant for a decision maker. Empirical tests show that the proposed method performs well with respect to the stated hypervolume objective.

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