Trade Space Exploration of a Wing Design Problem Using Visual Steering and Multi-Dimensional Data Visualization
Timothy W. Simpson, Daniel Edward Carlsen, Christopher Congdon, Gary M. Stump, Michael A. Yukish · 2008
Trade space exploration is a promising decision-making paradigm that provides a visual and intuitive means for formulating, adjusting, and ultimately solving multi-objective design optimization problems. This is achieved by combining multi-dimensional data visualization techniques with visual steering commands to allow designers to “steer” the optimization process while searching for the best, or Pareto optimal, designs. In this paper, we investigate the impact of constraint handling on the trade space exploration process. Specifically we consider three different constraint handling methods: (1) no constraint handling, (2) manual constraint handling, and (3) automatic constraint handling, and assess their impact on the efficiency and effectiveness of the visual steering commands used to explore the trade space. We find that the performance of the constraint handling method is highly correlated with the visual steering command that is being used and is consistent with the user’s a priori knowledge about the constraints, which is reflected in how constraints are handled in each method. The implications of these findings on the trade space exploration process are also discussed in conjunction with future work.