Optimal Policies for a Multi-Echelon Inventory Problem
Andrew J. Clark and
Herbert Scarf
Additional contact information
Andrew J. Clark: Planning Research Corporation, Los Angeles, California
Management Science, 1960, vol. 6, issue 4, 475-490
Abstract:
In the last several years there have been a number of papers discussing optimal policies for the inventory problem. Almost without exception these papers are devoted to the determination of optimal purchasing quantities at a single installation faced with some pattern of demand. It has been customary to make the assumption that when the installation in question requests a shipment of stock, this shipment will be delivered in a fixed or perhaps random length of time, but at any rate with a time lag which is independent of the size of the order placed. There are, however, a number of situations met in practice in which this assumption is not a tenable one. An important example arises when there are several installations, say 1, 2, ..., N, with installation 1 receiving stock from 2, with 2 receiving stock from 3, etc. In this example, if an order is placed by installation 1 for stock from installation 2, the length of time for delivery of this stock is determined not only by the natural lead time between these two sites, but also by the availability of stock at the second installation. In this paper we shall consider the problem of determining optimal purchasing quantities in a multi-installation model of this type.
Date: 1960
References: Add references at CitEc
Citations: View citations in EconPapers (324)
Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.6.4.475 (application/pdf)
Related works:
Journal Article: Optimal Policies for a Multi-Echelon Inventory Problem (2004) 
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:ormnsc:v:6:y:1960:i:4:p:475-490
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().