Name: Chris Monroe

Master’s Thesis Defense Meeting
Date: Tuesday, May 21st, 2019

Time: 12:00pm
Location: J.S. Coon Building, room 148
 
Advisor:
Associate Professor Rick Thomas, Ph.D. (Georgia Tech)
 
Thesis Committee Members:
Associate Professor Rick Thomas, Ph.D. (Georgia Tech)

Associate Professor James Roberts, Ph.D. (Georgia Tech)
Associate Professor Jamie Gorman, Ph.D. (Georgia Tech)

Title: Optimizing Military Planners Course of Action Decision-Making

Abstract

Military planners are faced with ever-increasing constraints, obstacles, and priority readjustments during the course of action (COA) development. This upward trajectory places a more demanding cognitive workload on decision makers, which only helps to further complicate their jobs. An effort to mediate workload is currently ongoing in the armed services through the development of effective systems that assist the planners in COA decision-making. I proposed an experiment that uses the Tool for Multi-Objective Planning and Asset Routing (TMPLAR) to aid decision makers through the use of route filtering (via sliders) and clustering (via scatter-gather) to support the selection of high utility routes while reducing route selection latency and associated workload. Study participants went through multiple levels of COA planning in a game-like scenario-driven computer application.  I predicted that filtering and clustering tools would enhance users to select the best route based on predetermined attribute weights that reflect commander intent. Also, this study delivered feedback on perceived workload from using TMPLAR. The overarching goal of this research was to improve our understanding of military decision making to assist military leaders in using supervisory control of an optimizer for accurate, efficient route planning.