A sequential statistics approach to dynamic staffing under demand uncertainty | IEEE Conference Publication | IEEE Xplore

A sequential statistics approach to dynamic staffing under demand uncertainty


Abstract:

Service systems are highly dependent on staffing decisions to provide satisfactory quality of service. This paper tackles the problem of decision making under uncertainty...Show More

Abstract:

Service systems are highly dependent on staffing decisions to provide satisfactory quality of service. This paper tackles the problem of decision making under uncertainty pertaining to the source of demand. Regardless of the distribution of the demand, the proposed staffing rule reacts to the requested quality of service to determine the quality of the estimators of the unknown demand-process parameters, as well as making optimal staffing decisions. Theoretical results on the consistency and optimality of the proposed method is illustrated using sequential statistics approaches.
Date of Conference: 03-06 December 2017
Date Added to IEEE Xplore: 08 January 2018
ISBN Information:
Electronic ISSN: 1558-4305
Conference Location: Las Vegas, NV, USA

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