Efficient Experimental Design Tools for Exploring Command and Control Organizational Structures

Abstract

Armed forces around the world are considering radical transformations to their structures and strategies because of the information revolution and the changing global environment. Senior leadership continually face decisions on how best to structure, modernize, organize, and employ forces in an increasingly uncertain future. For many of these problems analytical methods are not applicable, and large-scale experimentation is not feasible. Simulation provides a valuable tool for addressing these types of problems. One key characteristic of these decisions is the large number of factors, and interactions between factors that impact decision makers. Traditional simulation approaches are not designed to deal with this many factors, therefore the results are often incorrect or misleading. In this paper we introduce and implement efficient design of experiments techniques to analyze C2 organizational models and pursue optimal settings for different performance measures. This allows analysts to rapidly identify the important factors within the simulation, employ an experimental design to fully explore the simulation space efficiently, and design the systems with desired optimal performances with the simulation model. This effort dramatically increases the breadth and depth of insights possible when the simulation output data are analyzed, while reducing the time required for performing a study.