Multi-fidelity Accelerated Global Search (MAGS)

University Of Washington, Seattle WA

Investigators

Abstract

This award will promote the progress of science and contribute to the advancement of national prosperity and health by introducing new computational methods to guide the design and control of modern manufacturing facilities, such as complex bio-manufacturing processes that produce personalized medical treatments. High-fidelity simulation models that can be used to evaluate the performance of a manufacturing system are computationally intensive and often require expensive data collection, limiting their use. On the other hand, queueing models use less computation time but are less accurate. There is a substantial gap in understanding how to effectively make use of both high- and low-fidelity models to design and control such systems. This award supports advancing theoretical foundations and algorithm development for large-scale global optimization enabling the use of multiple models of varying accuracy and computational effort. This research will have broad impact on the growth of bio-manufacturing in the U.S., and will provide a diverse population of students with the education and training needed to deploy and extend these tools, advancing the national economic welfare. This project will create a new Multi-fidelity Accelerated Global Search (MAGS) framework for stochastic global optimization that will intelligently combine high- and low-fidelity models to dynamically allocate computational effort guided by statistical analysis of solution quality. The goal is to reduce the number of high-fidelity simulation evaluations by taking advantage of low-fidelity models, thus integrating model approximation (learning) with optimization (search). This research addresses algorithmic design, scalability, and finite-time stochastic analysis of MAGS. The project will provide a theoretical foundation for computational complexity and aid in deriving a dynamic and adaptable decomposition scheme to realize large-scale optimization. The design and operation of an individualized bio-manufacturing system will be used to test and refine MAGS throughout its development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.