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This paper describes two experiments exploring the potential of the Kriging methodology for constrained simulation optimization. Both experiments study an (s, S) inventory system with the objective of finding the optimal values of s and S. The goal function and constraints in these two experiments differ, as does the approach to determine the optimum combination predicted by the Kriging model. The results of these experiments indicate that Kriging offers opportunities for solving constrained optimization problems in stochastic simulation; future research will focus on further refining the methodology.
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