Simulation-based analysis and optimization of the United States Army performance appraisal system.

In this dissertation, a discrete event simulation framework is considered to replicate the dynamics, structure, and regulatory constraints placed on the officers in the U.S. Army. Using performance appraisal data provided by the United States Army Human Resources Command, we create a multi-objective response function that quantifies the human behavior associated with evaluating subordinates. Utilizing simulation-optimization techniques for model validation enables estimating unknown input parameters, such as human behavior, based on historical data. Furthermore, the model allows users to analyze the effects of current constraints on the evaluation system and the effects of proposed personnel policy changes.The effectiveness of the performance appraisal system is based on its ability to accurately evaluate the officers\u27 performance levels. An initial analysis showed that 20.07\% of the officers in the system do not receive as many above average evaluations as their performance level warrants. Additionally, structural changes such as decreasing the average number of a rater\u27s subordinates from fifteen to five increases the number of misidentified personnel by 59.86\%. Ranking and selection statistical procedures assist in determining the optimal combination of input parameters such as forced distribution constraints placed on raters, frequency of moves, number of subordinates assigned to each rater, and rater behavior. The simulation will serve as a tool for policy analysis to recommend policies and behavior that maximizes the extent to which the performance appraisal system accurately identifies the most qualified employees. Consequently, the results demonstrate broad applicability of simulation-optimization in the field of manpower modeling and human resource management