A combined procedure for optimization via simulation

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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