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Optimization of simulated systems is the goal of many methods, but most methods assume known environments. In this paper we present a methodology that does account for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by either Response Surface Methodology or Kriging metamodeling. We illustrate the resulting methodology through the well-known Economic Order Quantity (EOQ) model.
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Stored only when both papers are in the corpus — 43 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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