229
Views
20
CrossRef citations to date
0
Altmetric
Original Articles

Setting basestock levels in multi-product systems with setups and random yield

, &
Pages 1158-1170 | Received 01 May 2002, Accepted 01 Feb 2008, Published online: 22 Oct 2008
 

Abstract

This paper provides procedures for setting optimal, or near-optimal, basestock levels in a multi-product system with setups and random yield. The procedures are derived using a novel polling system model of the system that contains both queues for production orders and queues for temporary storage of rework orders with routing occurring between these two types of queues. Both systems with backlogging and lost sales are analyzed using existing work on polling models with routing and possibly finite buffers. For a system with backlogging, we provide a cost function that is minimized by solving a set of single-item newsvendor problems. In systems with lost sales, each queue is given a finite buffer equal to the basestock level and excess demand is lost. We provide a cost function and show that finding optimal solutions for large problems is not tractable; thus, we provide a heuristic for finding the basestock levels and demonstrate the effectiveness of the heuristic and accuracy of the cost approximation through numerical tests.

Acknowledgements

This research was supported in part by National Science Foundation grant DMI-9713727, and later by the Missouri Research Board. We would like to thank the associate editor and anonymous referees whose comments greatly improved this paper.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 202.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.