Technical Papers

Solving multi-objective optimization problems that involve computationally expensive
functions is a normal part of many engineering applications. Runtime issues are magnied
when one moves from a single discipline to multiple disciplines in a multidisciplinary design
optimization setting. The tools selected to perform a design space exploration within this
setting must be chosen with care.
Normal-Boundary Intersection (NBI) is a robust general purpose multi-objective opti-
mization method for design problems. In the setting of computationally expensive func-
tions, running NBI directly using the simulation requires a prohibitive amount of compu-
tational cost. Alternatively, running on a surrogate model approximation to the simulation
fails to produce suciently accurate solutions. Our approach combines the use of mod-
els and simulations in a way similar to the general surrogate management framework by
iteratively using both the models and the simulations. While this approach can be ex-
ecuted with the push of a button, it is best used, especially at the beginning of a new
problem, as one step in a larger design space exploration process. The process includes
the design, execution and analysis of computer experiments, surrogate model development,
single objective optimization and problem renement.
This paper outlines the surrogate model management framework approach to solving
multi-objective optimization problems within the context of a general design exploration
process. The importance of the use of data visualization techniques will be highlighted
in the discussion. We conclude with a representative aircraft design problem from the
aerospace industry.