Operations Research
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

OPERATIONS RESEARCH
Vol. 54, No. 3, May-June 2006, pp. 419-435
DOI: 10.1287/opre.1060.0285
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bassamboo, A.
Right arrow Articles by Zeevi, A.
Right arrow Search for Related Content

Design and Control of a Large Call Center: Asymptotic Analysis of an LP-Based Method

Achal Bassamboo, J. Michael Harrison, Assaf Zeevi

Kellogg School of Management, Northwestern University, Evanston, Illinois 60208
Graduate School of Business, Stanford University, Stanford, California 94305
Graduate School of Business, Columbia University, New York, New York 10027
a-bassamboo{at}northwestern.edu
harrison_michael{at}gsb.stanford.edu
assaf{at}gsb.columbia.edu

This paper analyzes a call center model with m customer classes and r agent pools. The model is one with doubly stochastic arrivals, which means that the m-vector {lambda} of instantaneous arrival rates is allowed to vary both temporally and stochastically. Two levels of call center management are considered: staffing the r pools of agents, and dynamically routing calls to agents. The system manager’s objective is to minimize the sum of personnel costs and abandonment penalties. We consider a limiting parameter regime that is natural for call centers and relatively easy to analyze, but apparently novel in the literature of applied probability. For that parameter regime, we prove an asymptotic lower bound on expected total cost, which uses a strikingly simple distillation of the original system data. We then propose a method for staffing and routing based on linear programming (LP), and show that it achieves the asymptotic lower bound on expected total cost; in that sense the proposed method is asymptotically optimal.

Subject classifications: stochastic model applications; call centers; queueing; dynamic routing; fluid limits; doubly stochastic; asymptotic analysis; discrete review; performance bounds; abandonments; staffing.
History: Received June 2004; revision received March 2005; accepted May 2005.




This article has been cited by other articles:


Home page
 Mathematics of Operations ResearchHome page
M. Akan and B. Ata
Bid-Price Controls for Network Revenue Management: Martingale Characterization of Optimal Bid Prices
Mathematics of Operations Research, November 1, 2009; 34(4): 912 - 936.
[Abstract] [PDF]

Home page
 Operations ResearchHome page
A. Mandelbaum and S. Zeltyn
Staffing Many-Server Queues with Impatient Customers: Constraint Satisfaction in Call Centers
Operations Research, September 1, 2009; 57(5): 1189 - 1205.
[Abstract] [PDF]

Home page
 Management ScienceHome page
G. Pang and W. Whitt
Service Interruptions in Large-Scale Service Systems
Management Science, September 1, 2009; 55(9): 1499 - 1512.
[Abstract] [PDF]

Home page
 Operations ResearchHome page
O. Baron and J. Milner
Staffing to Maximize Profit for Call Centers with Alternate Service-Level Agreements
Operations Research, May 1, 2009; 57(3): 685 - 700.
[Abstract] [PDF]

Home page
 Operations ResearchHome page
A. Bassamboo and A. Zeevi
On a Data-Driven Method for Staffing Large Call Centers
Operations Research, May 1, 2009; 57(3): 714 - 726.
[Abstract] [PDF]

Home page
 Mathematics of Operations ResearchHome page
C. W. Chan and V. F. Farias
Stochastic Depletion Problems: Effective Myopic Policies for a Class of Dynamic Optimization Problems
Mathematics of Operations Research, May 1, 2009; 34(2): 333 - 350.
[Abstract] [PDF]

Home page
 Operations ResearchHome page
I. Gurvich, M. Armony, and C. Maglaras
Cross-Selling in a Call Center with a Heterogeneous Customer Population
Operations Research, March 1, 2009; 57(2): 299 - 313.
[Abstract] [PDF]

Home page
 MSOMHome page
A. Bassamboo, J. M. Harrison, and A. Zeevi
Pointwise Stationary Fluid Models for Stochastic Processing Networks
MSOM, January 1, 2009; 11(1): 70 - 89.
[Abstract] [PDF]

Home page
 Mathematics of Operations ResearchHome page
R. Atar and A. Shwartz
Efficient Routing in Heavy Traffic Under Partial Sampling of Service Times
Mathematics of Operations Research, November 1, 2008; 33(4): 899 - 909.
[Abstract] [PDF]

Home page
 Management ScienceHome page
J. M. Milner and T. L. Olsen
Service-Level Agreements in Call Centers: Perils and Prescriptions
Management Science, February 1, 2008; 54(2): 238 - 252.
[Abstract] [PDF]

Home page
 Management ScienceHome page
I. Gurvich, M. Armony, and A. Mandelbaum
Service-Level Differentiation in Call Centers with Fully Flexible Servers
Management Science, February 1, 2008; 54(2): 279 - 294.
[Abstract] [PDF]

Home page
 Operations ResearchHome page
F. de Vericourt and O. B. Jennings
Dimensioning Large-Scale Membership Services
Operations Research, January 1, 2008; 56(1): 173 - 187.
[Abstract] [PDF]

Home page
 MSOMHome page
N. Gans and Y.-P. Zhou
Call-Routing Schemes for Call-Center Outsourcing
MSOM, January 1, 2007; 9(1): 33 - 50.
[Abstract] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2006 by INFORMS.