Friday, 16:15 - 16:40 h, Room: MA 042


Yehua Wei
Understanding the performance of the long chain and sparse designs in process flexibility

Coauthor: David Simchi-Levi


We study the expected sales of sparse flexibility designs, which are modeled by the expected objective value of a stochastic bipartite max-flow problem. In particular, we focus on the long chain design, a design that has been successfully applied by several industries. First, we uncover an interesting property of the long chain, supermodularity. Then, this property is used to show that the performance of the long chain is characterized by the difference between the expected sales of two simpler designs which leads to the optimality of the long chain among 2-flexibility designs. Finally, under IID demand, this characterization gives rise to three developments: (i) an effective algorithm to compute the expected sales of long chains using only matrix multiplications; (ii) a result that the gap between the fill rate of full flexibility and that of the long chain increases with system size, thus implying that the effectiveness of the long chain relative to full flexibility increases as the number of products decreases; (iii) a risk-pooling result implying that the fill rate of a long chain increases with the number of products, but this increase converges to zero exponentially fast.


Talk 3 of the contributed session Fri.3.MA 042
"Applications of supply chain" [...]
Cluster 13
"Logistics, traffic, and transportation" [...]


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