Analysis of the assignment scheduling capability for Unmanned Aerial Vehicles (ASC-U) simulation tool

Abstract

The U.S. Army Training and Doctrine Command (TRADOC) Analysis Center (TRAC) and the Modeling, Virtual Environments, and Simulations Institute (MOVES) at the Naval Postgraduate School, Monterey, California developed the Assignment Scheduling Capability for UAVs (ASC-U) simulation to assist in the analysis of unmanned aerial vehicle (UAV) requirements for the current and future force. ASC-U employs a discrete event simulation coupled with the optimization of a linear objective function. At regular intervals, ASC-U obtains an optimal solution to a simplified problem that assigns available UAVs to missions that are available or will be available within a future time horizon. This thesis simultaneously explores the effects of 26 simulation and UAV factors on the mission value derived when allocating UAVs to mission areas. The analysis assists in defining the near term (2008) UAV force structure and the investment strategy for the mid term (2013), and far term (2018). We combine an efficient experimental design, exploratory modeling, and data analysis to examine 514 variations of a scenario involving five UAV classes and over 21,000 mission areas. The conclusions suggest the following: the optimization interval significantly influences the quality of the solution, percent mission coverage may depend on a few UAV performance factors, small time horizons increase percent mission coverage, and carefully planned designs assist in the exploration of the outer and interior regions of the response surface.