Adaptive server staffing in the presence of time-varying arrivals: A feed-forward control approach

M. C. Testik, J. K. Cochran, George Runger

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

We study the short-term staffing problem of systems that experience random, non-stationary demand. The typical method to accommodate changes in arrival rate is to use historical data to identify peak periods and associated forecasting for upcoming time windows. In this paper, we develop a method that instead detects change as it happens. Motivated by an automatic call distributor system in a call centre with time-varying arrivals, we propose a change detection algorithm based upon non-homogeneous Poisson processes. The proposed method is general and may be thought of as a feed-forward strategy, in which we detect a change in the arrival process, estimate the new magnitude of the arrival rate, and assign an appropriate number of servers to the tasks. The generalized likelihood ratio statistic is used and a recommendation for its decision limit is developed. Simulation results are used to evaluate the performance of the detector in the context of a telephone call centre.

Original languageEnglish (US)
Pages (from-to)233-239
Number of pages7
JournalJournal of the Operational Research Society
Volume55
Issue number3
DOIs
StatePublished - Mar 2004

Keywords

  • Adaptive staffing
  • Generalized likelihood ratio statistic
  • Non-homogeneous Poisson process
  • Telephone call centres

ASJC Scopus subject areas

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

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