Near-Optimal Echelon-Stock (R, nQ) Policies in Multistage Serial Systems

Fangruo Chen and Yu-Sheng Zheng
Additional contact information
Fangruo Chen: Columbia University, New York, New York
Yu-Sheng Zheng: University of Pennsylvania, Philadelphia, Pennsylvania

Operations Research, 1998, vol. 46, issue 4, 592-602

Abstract: We study echelon-stock ( R , nQ ) policies in a multistage, serial inventory system with compound Poisson demand. We provide a simple method for determining near-optimal control parameters. This is achieved in two steps. First, we establish lower and upper bounds on the cost function by over- and under-charging a penalty cost to each upstream stage for holding inadequate stock. Second, we minimize the bounds, which are simple, separable functions of the control parameters, to obtain heuristic solutions. We also provide an algorithm that guarantees an optimal solution at the expense of additional computational effort. A numerical study suggests that the heuristic solutions are easy to compute (even for systems with many stages) and are close to optimal. It also suggests that a traditional approach for determining the order quantities can be seriously suboptimal. All the results can be easily extended to the discrete-time case with independent, identically distributed demands.

Keywords: Inventory/production; multiechelon; lot-sizing; stochastic; heuristics (search for similar items in EconPapers)
Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.46.4.592 (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:46:y:1998:i:4:p:592-602

Access Statistics for this article

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