Optimal capacity expansion for multi-product, multi-machine manufacturing systems with stochastic demand |
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Authors: | Feng Zhang Robin Roundy Metin akanyildirim Woonghee Tim Huh |
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Affiliation: |
a School of Operations Research and Industrial Engineering, Cornell University, Ithaca, NY, USA |
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Abstract: | We consider a discrete-time capacity expansion problem involving multiple product families, multiple machine types, and non-stationary stochastic demand. Capacity expansion decisions are made to strike an optimal balance between investment costs and lost sales costs. Motivated by current practices in the semiconductor and other high-tech industries, we assume that only minimal amounts of finished-goods inventories are held, due to the risk of obsolescence. We assume that when capacity is in short supply, management desires to ensure that a minimal service level for all product families is obtained. Our approach uses a novel assumption that demand can be approximated by a distribution whose support is a collection of rays emanating from a point and contained in real multi-dimensional space. These assumptions allow us to solve the problem as a max-flow, min-cut problem. Computational experiments show that large problems can be solved efficiently. |
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