1 Trade Space Exploration of Satellite Datasets Using a Design by Shopping Paradigm 1,2 Gary M. Stump Research Assistant The Applied Research Laboratory The Pennsylvania State University University Park, PA, USA 16802 Phone/Fax : (814) 863 – 9911/4128 Email : gms158@psu.edu Mike Yukish Head, Product & Process Design Department The Applied Research Laboratory The Pennsylvania State University University Park, PA, USA 16802 Phone/Fax : (814) 863 – 7143/4128 Email : mikeyukish@psu.edu Timothy W. Simpson Associate Professor Mechanical & Industrial Engineering The Pennsylvania State University University Park, PA, USA 16802 Phone/Fax : (814) 863 – 7136/4745 Email : tws8@psu.edu John J. O’Hara Assistant Research Engineer The Applied Research Laboratory The Pennsylvania State University University Park, PA, USA 16802 Phone/Fax : (814) 863 – 8122/4128 Email : jjo135@psu.edu 1 0-7803-8155-6/04/$17.00© 2004 IEEE 2 IEEEAC paper #1039, Version 1, Updated December 9, 2003 Abstract—One of the goals of early stage conceptual design is to execute broad trade studies of possible design concepts, evaluating them for their capability to meet minimum requirements, and choosing the one that best satisfies the goals of the project. To support trade space exploration, we have developed the Advanced Trade Space Visualizer (ATSV) that facilitates a design by shopping paradigm, which allows a decision-maker to form a preference a posteriori and use this preference to select a preferred satellite. Design automation has allowed us to implement this paradigm, since a large number of designs can be synthesized in a short period of time. The ATSV uses multi- dimensional visualization techniques, preference shading, and Pareto frontier display to visualize satellite trade spaces. Keywords—Multi-dimensional Data Visualization, Design by Shopping, Multiobjective Optimization TABLE OF CONTENTS ....................................................................... 1. INTRODUCTION .......................................1 2. MOTIVATION AND RELATED WORK ......2 3. ATSV INTERFACE ..................................2 4. TRADE SPACE EXPLORATION.................6 5. CONCLUSION ...........................................9 ACKNOWLEDGEMENTS ...............................9 REFERENCES ...............................................9 BIOGRAPHIES ............................................10 1. INTRODUCTION Traditional research on computational design methods has focused on optimization and its use in the design process. For complex systems design, the discipline of multidisciplinary design optimization (MDO) has risen to fill the need for design optimization. MDO itself rests on the extensive body of work in the theory of games and decisions, of which there is an extraordinary body of research. However, the strict focus on computational design optimization has a critical failing in that it requires designers to specify their preferences and constraints a priori and typically in a mathematical form that is alien to how humans actually think. In many cases this may be justified, such as when a preference can be easily distilled to a single metric, but problems arise in multi-objective analyses where the