A Grants Administration Application Identifying the Best Path to Optimality

This research addresses a grant administration workload-to-staff assignment problem that occurs in the Office of Research and Sponsored Programs (ORSP) at land-grant universities in the pre-award process. We first identify the... [ view full abstract ]

This research addresses a grant administration workload-to-staff assignment problem that occurs in the Office of Research and Sponsored Programs (ORSP) at land-grant universities in the pre-award process. We first identify the optimal (utopian) workload assignment plan using a mixed-integer linear programming problem. The optimal assignment of staff members to workload (academic departments) may differ considerably from the status quo, requiring multiple reassignments from the current state to reach optimality. The number of reassignments creates concerns related to loss of administrator-department relationship, loss of department-related knowledge, and increase in managerial inconvenience. In order to achieve the best workload reassignment with the fewest changes from the current status quo, while still placing a greater emphasis on the effective use of limited resources, we propose and illustrate a multiple objective optimization technique to identify the n best departmental reassignments from the current state that provide the greatest progress toward the utopian solution. Solving this problem over several values of n and plotting the results allows the decision maker to visualize the trade-off between the number of reassignments and the resulting progress achieved toward the utopian solution. This system supports the ORSP pre-award administrator in making an informed decision about the best number of reassignments (n) to choose based on an objective assessment of the relevant trade-offs.