Server staffing to meet time-varying demand

Otis B. Jennings; Avishai Mandelbaum; William A. Massey; Ward Whitt

doi:10.1287/mnsc.42.10.1383

Server staffing to meet time-varying demand

Otis B. Jennings, Avishai Mandelbaum, William A. Massey, Ward Whitt

Research output: Contribution to journal › Article › peer-review

173 Scopus citations

Abstract

We consider a multiserver service system with general nonstationary arrival and service-time processes in which s(t), the number of servers as a function of time, needs to be selected to meet projected loads. We try to choose s(t) so that the probability of a delay (before beginning service) hits or falls just below a target probability at all times. We develop an approximate procedure based on a time-dependent normal distribution, where the mean and variance are determined by infinite-server approximations. We demonstrate that this approximation is effective by making comparisons with the exact numerical solution of the Markovian M_t/M/ s_t model.

Original language	English (US)
Pages (from-to)	1383-1394
Number of pages	12
Journal	Management Science
Volume	42
Issue number	10
DOIs	https://doi.org/10.1287/mnsc.42.10.1383
State	Published - Oct 1996

All Science Journal Classification (ASJC) codes

Strategy and Management
Management Science and Operations Research

Keywords

Capacity Planning
Infinite-server Queues
Multiserver Queues
Nonstationary Queues
Operator Staffing
Queues
Queues with Time-dependent Arrival Rates

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10.1287/mnsc.42.10.1383

Cite this

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title = "Server staffing to meet time-varying demand",

abstract = "We consider a multiserver service system with general nonstationary arrival and service-time processes in which s(t), the number of servers as a function of time, needs to be selected to meet projected loads. We try to choose s(t) so that the probability of a delay (before beginning service) hits or falls just below a target probability at all times. We develop an approximate procedure based on a time-dependent normal distribution, where the mean and variance are determined by infinite-server approximations. We demonstrate that this approximation is effective by making comparisons with the exact numerical solution of the Markovian Mt/M/ st model.",

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year = "1996",

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AU - Jennings, Otis B.

AU - Mandelbaum, Avishai

AU - Massey, William A.

AU - Whitt, Ward

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N2 - We consider a multiserver service system with general nonstationary arrival and service-time processes in which s(t), the number of servers as a function of time, needs to be selected to meet projected loads. We try to choose s(t) so that the probability of a delay (before beginning service) hits or falls just below a target probability at all times. We develop an approximate procedure based on a time-dependent normal distribution, where the mean and variance are determined by infinite-server approximations. We demonstrate that this approximation is effective by making comparisons with the exact numerical solution of the Markovian Mt/M/ st model.

AB - We consider a multiserver service system with general nonstationary arrival and service-time processes in which s(t), the number of servers as a function of time, needs to be selected to meet projected loads. We try to choose s(t) so that the probability of a delay (before beginning service) hits or falls just below a target probability at all times. We develop an approximate procedure based on a time-dependent normal distribution, where the mean and variance are determined by infinite-server approximations. We demonstrate that this approximation is effective by making comparisons with the exact numerical solution of the Markovian Mt/M/ st model.

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KW - Infinite-server Queues

KW - Multiserver Queues

KW - Nonstationary Queues

KW - Operator Staffing

KW - Queues

KW - Queues with Time-dependent Arrival Rates

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Server staffing to meet time-varying demand

Abstract

All Science Journal Classification (ASJC) codes

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