Optimization-based decision support algorithms for a team-in-the-loop planning experiment

Asset assignment and scheduling algorithms were developed and implemented to support a team-in-the-loop planning experiment conducted at the Naval Postgraduate School (NPS) in March 2009. The experiment examined planning and information flows among three cells in an abstracted and simplified Maritime Operations Center (MOC). This paper describes two optimization-based modules that focused on the Future Operations (FOPS) cell´s planning activities. Module 1, a FOPS Planning Module, was a decision aid that presented the planners with N-best asset packages that would meet individual task requirements, while maximizing task execution accuracy. Module 2, a Scheduling Module, was an optimization-based scheduling algorithm that was used by experiment designers to set the conditions for the mission planning activity (e.g., asset types and numbers, task requirements and asset capabilities), and to assure that the tasks presented to the human planners would be achievable to a specified level of accuracy. A third module, termed Current Operations (COPS) Risk Analysis module, not discussed in detail here, was also implemented to assist COPS players on the consequences of redirecting assets from an ongoing task.