Staff scheduling in high volume service facilities with downgrading

Abstract

This paper discusses the problem of scheduling a multi-skilled workforce in service organizations where demand varies throughout the day, 7 days a week. The goal is to determine the optimal complement of workers so that demand is met without violating labor rules, union agreements, and company policies. It is assumed that each member of the workforce possesses a particular type of skill and can be categorized as either full-time, part-time, or temporary. Demand is specified by skill type, and in the downgrading analysis, a person in a higher skill category can be assigned a job in a lower skill category, but at the original rate of pay. We develop a mixed-integer linear programming model for this problem based on staffing requirements at US Postal Service mail Processing and Distribution Centers (P&DCs). The solution methodology involves the use of a commercial code to find daily shifts, and post-processing heuristics to construct 5-day a week schedules, allocate lunch breaks, and assign workers to jobs during the day. Results are presented for the Dallas P&DC where it is seen that considerable savings are possible when downgrading is implemented.

Acknowledgement

This work was supported by the National Science Foundation, under grant DMI-0218701.