We propose an optimization-via-simulation algorithm for use when the performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables may be subject to deterministic linear integer constraints. Our approach---which consists of a global guidance system, a selection-of-the-best procedure, and local improvement---is globally convergent under very mild conditions.
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Pichitlamken et al. (2003) studied this question.
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