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Bi-objective Ranking and Selection Using Stochastic Kriging
March 29, 2024, 4:43 a.m. | Sebastian Rojas Gonzalez, Juergen Branke, Inneke van Nieuwenhuyse
cs.LG updates on arXiv.org arxiv.org
Abstract: We consider bi-objective ranking and selection problems, where the goal is to correctly identify the Pareto optimal solutions among a finite set of candidates for which the two objective outcomes have been observed with uncertainty (e.g., after running a multiobjective stochastic simulation optimization procedure). When identifying these solutions, the noise perturbing the observed performance may lead to two types of errors: solutions that are truly Pareto-optimal can be wrongly considered dominated, and solutions that are …
abstract arxiv cs.lg identify optimization pareto ranking running set simulation solutions stat.ml stochastic type uncertainty
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