Surrogate Model Based Design Optimization Seminar

Engineering design is synonymous with the use of long running and computationally intensive simulations, which are employed in the search for optimal designs in the presence of multiple, competing objectives and constraints. The difficulty of this search is often exacerbated by numerical 'noise' and inaccuracies in simulation data and the frailties of complex simulations, that is they often fail to return a result. Surrogate-based optimization methods can be employed to solve, mitigate, or circumvent problems associated with such searches. This talk presents an introduction to surrogate model based optimization and examines key advantages of the method. We conclude with a demonstration of multi-objective sports technique optimization.