TY - GEN
T1 - Robustness of multi-objective optimal solutions to physical deterioration through active control
AU - Avigad, Gideon
AU - Eisenstadt, Erella
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - Evolutionary multi-objective
KW - Physical deterioration
UR - http://www.scopus.com/inward/record.url?scp=78650747444&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-17298-4_43
DO - 10.1007/978-3-642-17298-4_43
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AN - SCOPUS:78650747444
SN - 3642172970
SN - 9783642172977
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 394
EP - 403
BT - Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings
T2 - 8th International Conference on Simulated Evolution and Learning, SEAL 2010
Y2 - 1 December 2010 through 4 December 2010
ER -