This research has developed and computationally implemented the “Navy Recruiter Prediction and Optimization Model” (NRPOM). NRPOM can assist Navy Recruiting Command (NRC) with the assignment of recruiters to geographical areas across the U.S. Under given assumptions, NRPOM optimizes: (a) the allocation of a limited number of recruiters to candidate recruiting stations in a region; (b) the assignment of Zip codes to recruiting stations; and (c) the (fraction of) time recruiters should spend at each Zip code. The research has also developed a predictive tool that produces input data for the optimization. Experiments conducted on realisticallysized problems demonstrate that these tools can be used to guide NRC’s decisions. However, NRPOM has only been tested with notional data from the state of California, and for this case some of the required inputs have not been provided by NRC; instead, the authors have used estimations that have no guarantee of reflecting actual data. Thus, we believe that NRPOM is a starting point by which to approximate a truly optimal solution to the problem; however its development is not finalized yet.

This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE0605853N/2098). https://nps.edu/nrp

Approved for public release; distribution is unlimited.

Navy Recruiting Command