Semiconductor lot allocation using robust optimization
Tsan Sheng Ng,
Yang Sun and
John Fowler
European Journal of Operational Research, 2010, vol. 205, issue 3, 557-570
Abstract:
In this work, the problem of allocating a set of production lots to satisfy customer orders is considered. This research is of relevance to lot-to-order matching problems in semiconductor supply chain settings. We consider that lot-splitting is not allowed during the allocation process due to standard practices. Furthermore, lot-sizes are regarded as uncertain planning data when making the allocation decisions due to potential yield loss. In order to minimize the total penalties of demand un-fulfillment and over-fulfillment, a robust mixed-integer optimization approach is adopted to model is proposed the problem of allocating a set of work-in-process lots to customer orders, where lot-sizes are modeled using ellipsoidal uncertainty sets. To solve the optimization problem efficiently we apply the techniques of branch-and-price and Benders decomposition. The advantages of our model are that it can represent uncertainty in a straightforward manner with little distributional assumptions, and it can produce solutions that effectively hedge against the uncertainty in the lot-sizes using very reasonable amounts of computational effort.
Keywords: Semiconductor; supply; chain; Lot; assignment; Uncertainty; modeling; Robust; optimization; Generalized; Benders; Branch-and-price (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (6)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:205:y:2010:i:3:p:557-570
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