Performance Analysis of a Queue with Congestion-Based Staffing Policy

Zhe George Zhang ()
Additional contact information
Zhe George Zhang: Department of Decision Sciences, Western Washington University, Bellingham, Washington 98225; and Faculty of Business Administration, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada

Management Science, 2009, vol. 55, issue 2, 240-251

Abstract: This paper analyzes a waiting line system that is motivated by the operations of border-crossing stations between the United States and Canada. There are two main conflicting goals in such a system: high security level, which often leads to a longer line; and good customer service, which requires a shorter line. Thus, unlike other queueing systems, maintaining the average queue length within a certain range is the primary objective. This is achieved using a staffing policy, called "congestion-based staffing," or CBS, where the number of servers (inspection booths) is adjusted according to the queue length during a planning period. We first present an exact benchmark model of Markovian type based on the matrix-geometric solution. For practical CBS policies, we develop a set of closed-form formulas for the major performance measures based on regenerative cycle analysis and fluid limit approximation. Numerical examples show that these approximation formulas are simple, accurate, and robust for practitioners to use in designing CBS policies.

Keywords: congestion-based staffing; matrix-geometric solution; regeneration cycle; fluid limits approximation; Markovian queues; (e; n; N) policy; border-crossing station (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.1080.0914 (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:ormnsc:v:55:y:2009:i:2:p:240-251

Access Statistics for this article

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