Affordability Modeling in an Uncertain Environment

We propose to create a technology to improve Naval acquisition planning in a partially known environment, thereby reducing the negative impact of uncertainty, while simultaneously incorporating affordability as a fundamental constraint. Our decision support system will be flexible in its assumptions to facilitate replanning in response to changes faced by planners and warfare systems architects. It will contain a genetic algorithm based optimization module, to enable the efficient determination of near optimal decisions despite enormous numbers of alternatives and numerous complications involved in their evaluation. This planning support tool will be based on our theory of dependency modeling, which we have successfully applied to Naval combat systems assessment and Air Force aircraft allocation problems. The proposed Phase I research will enable the adaptation of our MAAP technology, developed under Air Force sponsorship, to assist in making technological decisions that impact the affordability and performance of current and projected Naval systems. This will form the foundation for a Phase II decision aid tool that will allow acquisition planners, be they Navy, other military, or commercial, to evaluate and compare candidate strategies for the optimal and affordable allocation of assets to varied and often uncertain system requirements.