179
Views
10
CrossRef citations to date
0
Altmetric
Original Articles

Parallel algorithm for setting WIP levels for multi-product CONWIP systems

&
Pages 4681-4693 | Received 01 Nov 2005, Published online: 22 Feb 2007
 

Abstract

Reducing work-in-process (WIP) inventory is continuing to be an important business need because of several factors including the need to reduce working capital. Numerous techniques have been suggested for WIP reduction, and CONWIP is a competitive algorithm for WIP reduction. Prior CONWIP algorithms have been primarily sequential algorithms and can be potentially incur significant computing time, especially when dealing with inventories for multiple products. The paper proposes a card-setting algorithm for multiple product types subject to routing and throughput requirements. The proposed algorithm searches the WIP space iteratively and the step-size is adaptively selected based on the known properties of multi-chain, multi-class, closed queuing networks. Furthermore, parallelization of this search algorithm across multiple processors is proposed where each processor searches a different segment of the WIP space while adaptively adjusting its step size for all product types to ensure fast convergence. The proposed parallel algorithm can take advantage of distributed computing architectures to speed-up the overall computation. An experimental implementation of the parallel algorithm using Message Passing Interface (MPI) over a high-speed network is described. Computational results demonstrate that the proposed parallel algorithm can be parallelized over eight to ten processors to obtain a speed-up of three to five.

Acknowledgements

Work was partially supported by National Science Foundation Grants DMI-9908267 and DMI-0075572, and a Ben Franklin Technology Partnership through a Center of Excellence grant to Center for Manufacturing Enterprise Integration.

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 973.00 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.