Quantitative decision support for upgrading complex systems of systems

The engineering of complex systems of systems has been receiving greatly increased amounts of attention in recent years. Within the Department of Defense, "system of systems" terminology is now widely used to describe how the successful, combined operation of many platforms, weapon systems, and communication systems is necessary to achieve an overall warfare objective, especially injoint operations.; Although the characteristics and system engineering challenges associated with systems of systems are becoming well understood, effective architecting approaches that enable cost/performance trades are still immature. A systematic approach to considering how best to upgrade specific, complex systems of systems is postulated and demonstrated. The process treats cost as the independent variable (CAIV) and seeks to find the "best" point design that may involve upgrading all component systems simultaneously, not just one at a time. The process has been demonstrated on a naval mine countermeasures (MCM) system of systems representation of sufficient complexity and detail to demonstrate the feasibility of the approach. The process formulates a constrained, nonlinear optimization problem whose objective function is a representation of the top-level measure of effectiveness (MOE), with constraints represented by functionalized Performance Based Cost Models, secondary MOEs, and technology-driven bounds on system measures of performance (MOPs). Both closed-form and simulation-based optimization approaches have been demonstrated and differences quantified, including the suboptimality of considering just one system at a time.; Due to the nature of complex system of systems interactions, implementation of this optimization technique on problems of national interest will require a simulation to represent the mapping of system MOPs to single system MOEs and on to the overarching system of systems MOE. A stochastic simulation of the MCM system of systems was therefore also implemented and optimized utilizing a constrained variant of the Simultaneous Perturbation Stochastic Approximation method.; This process therefore demonstrates a disciplined, quantitative approach to developing system of systems upgrade options for very complex situations, which can result in more effective and comprehensive systems acquisition and technology investment strategies. A secondary benefit is that the process can be used as a framework for the utilization of campaign-level simulations to support acquisition decisions.