MS Proposal by Chris Monroe

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Name: Chris Monroe

Master’s Thesis Proposal Meeting
Date: Wednesday, July 25th, 2018

Time: 1:00pm
Location: J.S. Coon Building, room 148
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


Military planners are faced with ever-increasing constraints, obstacles, and priority readjustments during 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 propose 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 will go through multiple levels of COA planning in a game-like scenario-driven computer application.  I predict that filtering and clustering tools will enhance users to select the best route based on predetermined attribute weights that reflect commander intent. Also, this study will deliver feedback on usability and perceived workload from using TMPLAR. The overarching goal of this research is to improve our understanding of military decision making to assist military leaders in using supervisory control of an optimizer for accurate, efficient route planning.


  • Workflow Status:Published
  • Created By:Tatianna Richardson
  • Created:07/10/2018
  • Modified By:Tatianna Richardson
  • Modified:07/10/2018