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An approach to simulation response optimization in which a simulation experiment is run in such a manner as to generate optimal solutions is presented. Once the stochastic sample path of a simulation run has been generated, it is sometimes possible to retrospectively solve a deterministic optimization problem or a closely related problem. As demonstrated with some examples from communications and manufacturing, this approach can greatly simplify both the simulation experiment and the simulation model.>
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Stored only when both papers are in the corpus — 38 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.