Staff planning and scheduling in the service industry: an application to US Postal Service mail processing and distribution centers
This research addresses weekly personnel planning and scheduling problems that arise at various service facilities staffed by full-time and part-time employees. In response to demand fluctuations, expected leave, training assignments, and other contingencies, weekly adjustments are often required to better match available personnel with demand over the planning horizon. Unlike manufacturing where uniform 8-hour shifts are the rule, service organizations may experience several busy periods during the day that do not fit a standard shift. In such cases, supervisors must adjust employee schedules by assigning overtime, increasing the number of part-time hours, and calling in temporary workers. The situation is complicated by union contracts, labor rules, and company policies. To find solutions that can be implemented in a real-world environment, a two-phase approach was developed. In the first phase, the adjustment problem is formulated as a large-scale integer program and solved to generate the adjusted shift schedules. In the second phase, the shift schedules are post-processed to provide daily task assignments for each worker. An integrated model that combines the shift scheduling and task assignment is also proposed to incorporate base group requirements and movement restrictions. Since only relatively small problems could be solved by commercial solver, two decomposition heuristics––network splitting and column generation––were designed to deliver good feasible solutions in a more timely manner. In conjunction with this problem, the impact of the workgroup restrictions on long-term staff planning was also investigated. An analysis of the problems is presented for an application involving weekly and long-term scheduling at a mail processing and distribution center. The results indicate that high quality solutions can be obtained within a reasonable amount of time.