Improving Navy recruiting with the new Planned Resource Optimization Model with Experimental Design (PROM-WED)
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Authors
Hogarth, Allison R.
Subjects
Navy recruiting
data farming
design of experiments
optimization
data farming
design of experiments
optimization
Advisors
Lucas, Thomas
McLemore, Connor
Date of Issue
2017-03
Date
Mar-17
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
The Navy spends over $300 million per year to recruit approximately 35,000 new active duty enlisted Sailors. The Navy has historically used a non-linear optimization model, the Planned Resource Optimization (PRO) model, to help inform decisions on the allocation of those recruiting resources. Input variables to the PRO model include economic influences and policy factors. The result is a recommended allocation of resources for advertisements, recruiters, enlistment bonuses, and education incentives. The PRO model's primary limitations are (1) potential deviations of input variables are not taken into consideration, and (2) extensive experimentation is not feasible. Realistically, input variables to the PRO model fluctuate, are unpredictable, and can interact with other variables to influence the recruiting environment and affect the optimal allocation of recruiting resources. This paper describes the Planned Resource Optimization Model with Experimental Design (PROM-WED), a tool that alleviates the limitations and enhances the analytic utility of the legacy PRO model. PROM-WED embeds the legacy PRO model within a data farming environment. PROM-WED's graphical user interface and decision support capability provide decision makers with robust insights into variable interactions and uncertainties to better inform their recruiting resourcing decisions.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
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NPS Report Number
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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.