Date of Award

3-24-2016

Document Type

Thesis

Degree Name

Master of Science in Operations Research

Department

Department of Operational Sciences

First Advisor

Matthew J.D. Robbins, PhD.

Abstract

The United States Air Force (USAF) is concerned with managing its officer corps to ensure sufficient personnel for mission readiness. Manpower planning for the USAF is a complex process which requires making decisions about accessions. Uncertainty about officer retention complicates such decisions. We formulate a Markov decision process model of the Air Force officer manpower planning problem (AFO-MPP) and utilize a least squares approximate policy iteration algorithm as an approximate dynamic programming (ADP) technique to attain solutions. Computational experiments are conducted on two AFO-MPP instances to compare the performance of the policy determined with the ADP algorithm to a benchmark policy. We find that the ADP algorithm performs well for the basis functions selected, providing policies which reduce soft" costs associated with shortages and surpluses in the force.

AFIT Designator

AFIT-ENS-MS-16-M-092

DTIC Accession Number

Pending

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