Order-Based Cost Optimization in Assemble-to-Order Systems

Yingdong Lu () and Jing-Sheng Song ()
Additional contact information
Yingdong Lu: IBM T. J. Watson Research Center, Yorktown Heights, New York 10598
Jing-Sheng Song: Fuqua School of Business, Duke University, Durham, North Carolina 27708

Operations Research, 2005, vol. 53, issue 1, 151-169

Abstract: We study a multi-item stochastic inventory system in which customers may order different but possibly overlapping subsets of items, such as a multiproduct assemble-to-order system. The goal is to determine the right base-stock level for each item and to identify the key driving factors. We formulate a cost-minimization model with order-based backorder costs and compare it with the standard single-item, newsvendor-type model with item-based backorder cost. We show that the solution of the former can be bounded by that of the latter with appropriately imputed parameters. Starting with this upper bound, the optimal base-stock levels of the order-based problem can be obtained in a greedy fashion. We also show that the optimal base-stock levels increase in replenishment lead times but may increase or decrease in lead-time variability and demand correlation. Finally, we devise closed-form approximations of the optimal base-stock levels to see more clearly their dependence on the system parameters.

Keywords: inventory/production:stochastic; multi-item; assemble-to-order; component commonality; probability:multivariate Poisson process; correlation; optimization:submodular function minimization (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (41)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.1040.0146 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:53:y:2005:i:1:p:151-169

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().