Name
Abstract | ||
|---|---|---|
This paper presents novel robustness measures to analyse and compare the robustness of solutions for constrained optimisation problems in the field of engineering design optimisation. First, we define uncertainty in production processes and present a method to quantify uncertainty. Based on the variations of a solution that are introduced by uncertainty, we want to assess the robustness of those solutions towards those variations. We show how a solutionu0027s quality and feasibility (with regards to constraint violation) change with increasing uncertainty and discuss how those changes determine the robustness of that solution. Furthermore, we present a method of aggregating that information into a single, real-valued robustness measure. This novel robustness measure can be used to select solutions that have a high robustness along with a high quality. To test the presented measures extensively, we apply them to various solutions for benchmark problems from published literature in the field of engineering desi... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1504/IJSPM.2018.093757 | IJSPM |
Field | DocType | Volume |
Mathematical optimization,Systems engineering,Robustness (computer science),Engineering design process,Constraint violation,Engineering | Journal | 13 |
Issue | Citations | PageRank |
4 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Philipp Fleck | 1 | 3 | 2.06 |
| Michael Kommenda | 2 | 97 | 15.58 |
| Thorsten Prante | 3 | 326 | 26.63 |
| Michael Affenzeller | 4 | 339 | 62.47 |