Solving Semi-Open Queuing Networks

Jing Jia () and Sunderesh S. Heragu ()
Additional contact information
Jing Jia: Barclays Bank of Delaware, Wilmington, Delaware 19801
Sunderesh S. Heragu: Department of Industrial Engineering, University of Louisville, Louisville, Kentucky 40292

Operations Research, 2009, vol. 57, issue 2, 391-401

Abstract: A semi-open queuing network (SOQN) is a special type of a queuing network consisting of two parts: an inner network with a population constraint and an external queue to accommodate jobs whose entrance is delayed. We first study an SOQN with a single class of jobs in tandem configuration and then extend our study to multiclass configurations. Multiclass SOQNs fall into two categories: general pallet and dedicated pallet SOQNs. For the general pallet case, we aggregate all classes and solve the resulting single-class SOQN. For the dedicated pallet case, we construct a method based on an existing product-form approximation method for general, multiclass closed networks. Our approximation method combines the matrix-geometric method with the decomposition-aggregation approach. Numerical results show that our approximations have desirable accuracy and efficiency.

Keywords: semi-open queuing network; multiple class; general pallet; dedicated pallet; tandem line; matrix-geometric method; experimental results (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.1080.0627 (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:57:y:2009:i:2:p:391-401

Access Statistics for this article

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