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The rate of change in technology in the semiconductor industry has made the demand supply planning process extremely challenging for manufacturers. This problem is further exacerbated for tool procurement because the tools are made to order, very expensive and have a long lead time for delivery. In this paper, we present a scenario-based stochastic planning approach for tool procurement under uncertainty in demand and formulate the problem as a mixed integer program. Our results based on the data from a manufacturing line indicate that the heuristics for stochastic planning can significantly outperform deterministic planning.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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