Analysis of uncertainty in engineering design optimization problems

In this paper, we analyze popular benchmark instances in the field of engineering design optimization regarding the robustness of published solutions. First, we implement selected benchmark problems with HeuristicLab and show the advantages of having a framework that enables rapid prototyping for optimization and analysis. Then, we show that many solutions quickly become infeasible when considering uncertainty like production inaccuracies. Based on these findings, we motivate why robust solutions for engineering design are important and present methods for measuring, identifying and visualizing robustness. Finally, we present how solutions can be compared and selected using a novel robustness measure.

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