Enabling the Design of Large-Scale Complex Engineered Systems using Self-Organizing Optimization Algorithms

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

The design of complex engineered systems is of critical importance to society due to the impact these systems have on productivity and quality of life. The complexity of systems such as electronic appliances, aircraft, spacecraft, or cars has grown tremendously as the expectations for performance and functionality continue to increase. The process for designing engineered systems has itself become complex, to the point where this complexity is becoming unmanageable. This award supports research on new approaches for designing that can tackle problems of unprecedented complexity through the use of optimization algorithms. Using optimization software, an automotive engineer can already design a car that maximizes the fuel economy by varying the car shape, dimensions, and engine characteristics, while satisfying all safety constraints. However, for engineered systems that involve large numbers of components and parameters that depend on each other, existing optimization algorithms become unacceptably slow. The objective of this project is to develop a new set of computational design optimization algorithms that will be able to optimize large-scale complex engineered systems in a scalable way. This scalability will be achieved by taking advantage of high-performance parallel computing resources and by exploiting the mathematical structure of the problem, decomposing it automatically into manageable components. The algorithms will be built upon recent mathematical developments that unify numerical methods for the solution and sensitivity analysis of coupled systems. The developed algorithms will be tested in collaboration with the National Aeronautics and Space Administration for the design optimization of a satellite and its operation. The resulting software will be of general purpose, and will be published under an open source license agreement.