Readiness and Resources in the U.S. Army Reserve. A Research Study Plan.

Abstract

This report details a research study plan for measuring unit readiness within the U.S. Army Reserve. A review is undertaken of the current measures of operational readiness which can be categorized as assets reporting (SORTS reporting), unit modeling (Monte Carlo simulations), and functional tests (field exercises). Four key issues in Reserve readiness are identified: personnel turbulence and unit cohesion, quality of leadership, quality of training, and Reserve unit location with respect to high potential markets. A conceptual model of reserve readiness is presented for studying these issues which addresses resources, indicators of readiness, and readiness metrics according to Beus' classification of mobilization, structural, and operational readiness. In concert with this conceptual model, an evolutionary simulation approach is proposed which relies upon genetic algorithms to generate dynamic, emergent measures of readiness rather than relying upon the subjective, static measures derived from SORTS data. Two research strategies are proposed: one for operational readiness and one for structural readiness. The first strategy has three steps: developing critical path MOS profiles for Army Reserve CFP units, determining the attrition/turnover by unit for the critical success MOS profiles, and then building a genetic simulation for generating emergent measures of unit readiness. The structural readiness research plan requires use of a geographic information system (GIS) for visual exploration of market supportability data which will lead to an analytical model for determining Reserve unit locations in high potential supportable markets.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1995
Accession Number
ADA300370

Entities

People

  • Daniel R. Dolk

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Attrition
  • Classification
  • Department Of Defense
  • Game Theory
  • Genetic Algorithms
  • Geographic Information Systems
  • Information Science
  • Information Systems
  • Leadership
  • Mobilization
  • Monte Carlo Method
  • Operational Readiness
  • Simulations
  • Social Sciences
  • Statistical Analysis
  • Training

Readers

  • Artificial Intelligence
  • Logistics and Supply Chain Management.
  • Naval Personnel Management

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy
  • Biotechnology