A simulation model for determining variable worker requirements in a service operation with time-dependent customer demand

Performance Analysis of Time-Dependent Queueing Systems: Survey and Classification

“…Stolletz [204] uses the SBC to analyze the performance of check-in counters. As another type of service counter with time-dependent arrivals, a fast food restaurant is studied by Kwan et al [137]. Foote [74] evaluates the performance of a drive-in banking facility with multiple lines involving jockeying.…”

“…Horonjeff [100] x FLUID Paullin and Horonjeff [184] x FLUID Foote [74] x SIPP de Neufville and Grillot [55] x FLUID Kolesar [128] x SIPP Kwan et al [137] x x SIPP Wirasinghe and Shehata [232] x FLUID Wirasinghe and Bandara [231] x x FLUID Thompson [214] x SIPP de Barros and Tomber [53] x FLUID Liu and Wein [141] x MOL, PSA Zhang [241] SIPP Stolletz [204] SBC…”

The Critical Few Minutes in Scheduling Time‐Varying Queuing Systems

“…He pointed out that because customers are not always served in the period in which they arrive, the effective arrival rate in each period needs to be modified to reflect this transfer of demand among periods, and he presents an algorithmic method for doing so. Jennings, Mandelbaum, Massey, and Whitt (1996) suggested an approximation procedure based on an infinite-server system, but a more general way to address the nonstationarity issue is to use simulation to reflect the nonstationary arrivals (e.g., see Brigandi, Dargon, Sheehan, & Spencer, 1994;Kwan, Davis, & Greenwood, 1988;Thompson 1995). Once service requirements are established for each planning period (regardless of how the requirements are obtained), many good methods exist for creating schedules that assign workers to these planning periods (see Thompson, 1997, for an extensive bibliography of mathematical programming approaches and Ingolfsson, Haque, & Umnikov, 2002, for an innovative genetic algorithm approach).…”

Approximation of the non-stationary M(t)/M(t)/c(t)-queue using stationary queueing models: The stationary backlog-carryover approach

“…The SIPP approach works accurately if the delays in consecutive time intervals are statistically independent of each other, the system achieves a steady-state in each interval, and the arrival rate does not change during a period (see Green et al, 2001). For underloaded systems with a high quality of service, the SIPP approach approximates the performance measures of the dynamic system well, see Gans et al (2003), Green et al (2007), and Kwan et al (1988). A problem of such a steady-state analysis is that for each period the demand rate must be strictly smaller than the service rate, i.e., overloading is prohibited.…”