United States Air Force Officer Manpower Planning Problem via Approximate Dynamic Programming

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, with the uncertainty about factors which could affect employee turnover. We formulate a Markov decision process model of the Air Force officer manpower planning problem (AFO-MPP). We utilize the least squares approximate policy iteration algorithm as an approximate dynamic programming (ADP) technique to solve this large-scale problem. We test the performance of the policy determined with the ADP algorithm compared to a benchmark policy on two problem instances of the AFO-MPP. We find that the algorithm performs well for the basis functions selected, providing policies which reduce "soft" costs associated with shortages and surpluses in the force.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 24, 2016
Accession Number
AD1053949

Entities

People

  • Amelia E Bradshaw

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Attrition
  • Computational Science
  • Department Of Defense
  • Dynamic Programming
  • Employment
  • Enlisted Personnel
  • Experimental Design
  • General Officers
  • Governments
  • Military Operations
  • Military Training
  • Operations Research
  • Personnel Management
  • Probability
  • United States

Readers

  • Naval Personnel Management
  • Operations Research