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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Robustness of Multi-objective Optimal Solutions to Physical Deterioration through Active Control
verfasst von : Gideon Avigad, Erella Eisenstadt
Erschienen in: Simulated Evolution and Learning
Verlag: Springer Berlin Heidelberg
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In this paper, we suggest a novel problem within the context of multi objective optimization. It concerns the control of solutions’ performances in multi objective spaces. The motivation for controlling these performances comes from an inspiration to improve the robustness of solutions to physical deterioration. When deterioration occurs, the solution performances degrade. In order to prevent extended degradation and loss of robustness, an active control is implemented. Naturally, in order to enable such a control, the solution (product) should have tunable parameters that would serve as the controlled variables. Optimizing the solution for such a problem means that the tunable parameters should be found and their manipulation determined. Here the optimal solutions and the controller are designed using multi and single objective evolutionary algorithms. The paper is concluded with a discussion on the high potential of the approach for research and real life applications.