An Optimization Approach to Balancing Risk and Cost in Combatant Command Capability Advocacy

Abstract

Unified Combatant Commands (UCCs) have broad continuing missions around the globe where they are tasked to provide functional expertise and defense of geographical areas.  Accomplishing these missions requires a robust portfolio of military capabilities (e.g., aircraft, spacecraft, command and control systems, radar systems).  UCCs routinely perform analyses to identify gaps between capabilities required to accomplish their mission and those currently at their disposal.  Each year they submit a prioritized list of required capabilities, including new systems and greater capacity with existing systems, to the Joint Staff in the costly and time-consuming Integrated Priority List (IPL) process.  This process relies on operational art and subject matter expertise, and sometimes fails to identify acquisition opportunities that achieve an optimal balance between risk and cost.  Because this IPL process affects all of the DOD’s personnel, material, systems and missions, it is arguably the most significant analytic challenge faced by the United States military.  This article presents an integer linear programming model that computes an optimal balance between operational risk and the cost of acquiring new capabilities, and allows decision makers to identify the real-world impact of their budgetary decisions.  We apply this model to the mission of providing aerospace defense of the United States and illustrate through sensitivity analysis the meaningful insights that can be gained by studying the relationship between the risk of not achieving 100 percent radar coverage and the opportunity cost of advocating for new capabilities.