OPTIMIZING NAVY RECRUITER ALLOCATION
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Authors
Murrell, Joshua P.
Subjects
optimization
statistical modeling
mixed-integer linear programming
statistical modeling
mixed-integer linear programming
Advisors
Salmeron-Medrano, Javier
Date of Issue
2023-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Navy Recruiting Command (NRC) assigns recruiters to recruiting stations across the country. A station’s demographics, historical data, and number of recruiters assigned are important considerations that affect the number of recruits signed. Naturally, some stations are more suitable for signing recruits than others. The current allocation process used by NRC is guided primarily by previous market share from each station. This process fails to consider unique characteristics about a station and the number of recruiters invested in order to achieve the result. Consequently, some stations might be underperforming relative to their potential while others might be able to perform at nearly the same level with fewer recruiters. This thesis proposes a model that estimates the number of recruits signed by a station as a function of the number of recruiters assigned with parameters that capture the unique characteristics of each station. The estimates from this model inform a mathematical optimization model whose objective maximizes expected recruits signed. The results of the optimization give a solution for recruiter allocation. We identify an allocation solution that results in more expected recruits signed than the current number of recruits signed.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
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Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.