Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ejor.2010.01.021
Title: Semiconductor lot allocation using robust optimization
Authors: Ng, T.S. 
Sun, Y.
Fowler, J.
Keywords: Branch-and-price
Generalized Benders
Lot assignment
Robust optimization
Semiconductor supply chain
Uncertainty modeling
Issue Date: 16-Sep-2010
Source: Ng, T.S., Sun, Y., Fowler, J. (2010-09-16). Semiconductor lot allocation using robust optimization. European Journal of Operational Research 205 (3) : 557-570. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ejor.2010.01.021
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. © 2010 Elsevier B.V.
Source Title: European Journal of Operational Research
URI: http://scholarbank.nus.edu.sg/handle/10635/63306
ISSN: 03772217
DOI: 10.1016/j.ejor.2010.01.021
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