Optimal allocation of employee resources to meet staffing demands

Eli Towle, Kane Mach


Throughout each summer, the University of Wisconsin - Stevens Point plays host to a variety of conferences. Each week, staffing needs for ten residence halls can change dramatically, depending on the duration and scope of each con- ference. Motivated by the inefficiency and marginal inaccuracy of creating schedules by hand, the summer conference coordinator inquired if a mathematical model could be built to automate and optimize the staffing process. As a result, a mixed-integer linear program was produced using AMPL (A Mathematical Programming Language). It is capable of better utilizing the staffing resources available to the university by accurately meeting all staffing requirements stip- ulated by the summer conference coordinator. These include daily and weekly hour restrictions, honoring approved individual requests for time off, and limiting the number of shifts for each worker. The most important parameter is ensuring every hall is properly staffed at each hourly interval. The solution was a great improvement to previous schedules generated by hand, as evidenced by the objective function of the program. Overall, the mathematical model met all requirements while successfully minimizing the number of scheduled secondary employees, reducing the total number of double shifts, and distributing hours evenly. This model can be applied to other institutions or businesses where specific amounts of workers are required at different time intervals throughout the day, and tailored to reflect which soft constraints the entity is foremost concerned with addressing.


Optimization; Scheduling; Mixed Integer Linear Programming

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