Trade space exploration is a promising decision-making paradigm that provides a visual and more intuitive means for formulating, adjusting, and ultimately solving 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 compare the performance of different combinations of visual steering commands implemented by two users to a multi-objective genetic algorithm that is executed “blindly” on the same problem with no human intervention. The results indicate that the visual steering commands — regardless of the combination in which they are invoked — provide a 4x–7x increase in the number of Pareto solutions that are obtained when the human is “in-the-loop” during the optimization process. As such, this study provides the first empirical evidence of the benefits of interactive visualization-based strategies to support engineering design optimization and decision-making. Future work is also discussed.

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