Evolutionary Design Optimization for Guided Weapon Concepts Modeling and Simulation

When the United States enters conflicts throughout the world, guided weapons that can eliminate threats while minimizing collateral damage are a necessity for all branches of the DoD. Each weapon is designed for a specific mission, though there is no guarantee that the design is either optimized for that mission or robust to mission changes. The scope of the design parameter space and the ever-evolving missions requiring guided weapons make accomplishing one or both tasks extremely challenging for current design practices. As computational power continues to increase, novel optimization methods that efficiently navigate such highly complex, large, multi-disciplinary design parameter spaces and fitness calculation become a more feasible solution to this problem. Evolutionary algorithms mimic natures approach to developing complex systems through generations of design variations and provide a novel means to optimize design. To this end, the team of Systems Technology, Inc. (STI) and the University of Tennessee Space Institute (UTSI) proposes to develop the Design Algorithm Robust Weapon Interface (DARWIN), a design interface that provides a robust, evolutionary multi-objective/multi-disciplinary optimizer, a design and visualization interface, and an architecture that utilizes modeling and simulation capabilities to evaluate the performance and improve the design from one generation to the next.