Optimal staffing policy: A service system with stochastic travel times

M. Al-Foraih; P. Johnson; G. Evatt; P. Duck

doi:10.5220/0004276902580263

Optimal staffing policy: A service system with stochastic travel times

M. Al-Foraih, P. Johnson, G. Evatt, P. Duck

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Private sector operators of response services such as ambulance, fire or police etc. are often regulated by targets on the distribution of response times. This may result in inefficient overstaffing to ensure those targets are met. In this paper, we use a network chain of M/M/K queues to model the arrival and completion of jobs on the system so that quantities such as the expected total time waiting for all jobs can be calculated. The Markov nature enables us to evoke the Hamilton Jacobi Bellman equation (HJB) principle to optimize the required number of staff whilst still meeting targets.

Original language	English
Title of host publication	ICORES 2013 - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems\|ICORES - Proc. Int. Conf. Oper. Res. Enterp. Syst.
Pages	258-263
Number of pages	5
DOIs	https://doi.org/10.5220/0004276902580263
Publication status	Published - 2013
Event	2nd International Conference on Operations Research and Enterprise Systems, ICORES 2013 - Barcelona Duration: 1 Jul 2013 → … http://dx.doi.org/10.5220/0004219200760081

Conference

Conference	2nd International Conference on Operations Research and Enterprise Systems, ICORES 2013
City	Barcelona
Period	1/07/13 → …
Internet address	http://dx.doi.org/10.5220/0004219200760081

Keywords

Network Queues
Stochastic Models
Time-Varying Queues
Workforce Staffing

Access to Document

10.5220/0004276902580263

Cite this

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title = "Optimal staffing policy: A service system with stochastic travel times",

abstract = "Private sector operators of response services such as ambulance, fire or police etc. are often regulated by targets on the distribution of response times. This may result in inefficient overstaffing to ensure those targets are met. In this paper, we use a network chain of M/M/K queues to model the arrival and completion of jobs on the system so that quantities such as the expected total time waiting for all jobs can be calculated. The Markov nature enables us to evoke the Hamilton Jacobi Bellman equation (HJB) principle to optimize the required number of staff whilst still meeting targets.",

keywords = "Network Queues, Stochastic Models, Time-Varying Queues, Workforce Staffing",

author = "M. Al-Foraih and P. Johnson and G. Evatt and P. Duck",

year = "2013",

doi = "10.5220/0004276902580263",

language = "English",

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pages = "258--263",

booktitle = "ICORES 2013 - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems|ICORES - Proc. Int. Conf. Oper. Res. Enterp. Syst.",

note = "2nd International Conference on Operations Research and Enterprise Systems, ICORES 2013 ; Conference date: 01-07-2013",

url = "http://dx.doi.org/10.5220/0004219200760081",

}

Al-Foraih, M, Johnson, P , Evatt, G & Duck, P 2013, Optimal staffing policy: A service system with stochastic travel times. in ICORES 2013 - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems|ICORES - Proc. Int. Conf. Oper. Res. Enterp. Syst.. pp. 258-263, 2nd International Conference on Operations Research and Enterprise Systems, ICORES 2013, Barcelona, 1/07/13. https://doi.org/10.5220/0004276902580263

Optimal staffing policy: A service system with stochastic travel times. / Al-Foraih, M.; Johnson, P.; Evatt, G. et al.
ICORES 2013 - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems|ICORES - Proc. Int. Conf. Oper. Res. Enterp. Syst.. 2013. p. 258-263.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Duck, P.

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N2 - Private sector operators of response services such as ambulance, fire or police etc. are often regulated by targets on the distribution of response times. This may result in inefficient overstaffing to ensure those targets are met. In this paper, we use a network chain of M/M/K queues to model the arrival and completion of jobs on the system so that quantities such as the expected total time waiting for all jobs can be calculated. The Markov nature enables us to evoke the Hamilton Jacobi Bellman equation (HJB) principle to optimize the required number of staff whilst still meeting targets.

AB - Private sector operators of response services such as ambulance, fire or police etc. are often regulated by targets on the distribution of response times. This may result in inefficient overstaffing to ensure those targets are met. In this paper, we use a network chain of M/M/K queues to model the arrival and completion of jobs on the system so that quantities such as the expected total time waiting for all jobs can be calculated. The Markov nature enables us to evoke the Hamilton Jacobi Bellman equation (HJB) principle to optimize the required number of staff whilst still meeting targets.

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KW - Stochastic Models

KW - Time-Varying Queues

KW - Workforce Staffing

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DO - 10.5220/0004276902580263

M3 - Conference contribution

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ER -

Optimal staffing policy: A service system with stochastic travel times

Abstract

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Keywords

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