A sequential statistics approach to dynamic staffing under demand uncertainty

摘要

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.