On component commonality for periodic review assemble-to-order systems

被引:0
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作者
Antoine Deza
Kai Huang
Hongfeng Liang
Xiao Jiao Wang
机构
[1] McMaster University,Advanced Optimization Laboratory, Department of Computing and Software
[2] McMaster University,DeGroote School of Business
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关键词
Assemble-to-order; Component commonality; Stochastic programming; Inventory replenishment; Component allocation;
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摘要
Akçay and Xu (Manag Sci 50(1):99–116, 2004) studied a periodic review assemble-to-order (ATO) system with an independent base stock policy and a first-come-first-served allocation rule, where the base stock levels and the component allocation are optimized jointly. The formulation is non-convex and, thus theoretically and computationally challenging. In their computational experiments, Akçay and Xu (Manag Sci 50(1):99–116, 2004) modified the right hand side of the inventory availability constraints by substituting linear functions for piece-wise linear ones. This modification may have a significant impact for low budget levels. The optimal solutions obtained via the original formulation; that is, without the modification, include zero base stock levels for some components and indicate consequently a bias against component commonality. We study the impact of component commonality on ATO systems. We show that lowering component commonality may yield a higher type-II service level. The lower degree of component commonality is achieved via separating inventories of the same component for different products. We substantiate this property via computational and theoretical approaches. We show that for low budget levels the use of separate inventories of the same component for different products could achieve a higher reward than with shared inventories. Finally, considering a simple ATO system consisting of one component shared by two products, we characterize the budget ranges such that the use of separate inventories is beneficial, as well as the budget ranges such that component commonality is beneficial.
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页码:29 / 46
页数:17
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