Most labor staffing and scheduling models assume a deterministic labor supply. For industries with even moderate turnover or absenteeism, this assumption may be quite costly. We present a labor scheduling model that accounts for the day-to-day flux of employees and capacity induced by voluntary resignations, new hires, training programs, and absenteeism. Our computational studies reveal that, compared with conventional stochastic labor scheduling models, the proposed technique can increase expected profits by 25 percent or more.
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