Details
| Original language | English |
|---|---|
| Medium of output | Poster |
| Place of Publication | Hannover |
| Publication status | Published - May 2019 |
Abstract
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Hannover. 2019.
Research output: Other contribution › Other publication › Research
}
TY - GEN
T1 - A novel multiple surrogate multi-objective decision making optimization algorithm and its application in induction heating
AU - Baldan, Marco
AU - Nacke, Bernard
AU - Nikanorov, Alexandre
PY - 2019/5
Y1 - 2019/5
N2 - We improved iTDEA, an existing preference-based multi-objective evolutionary algorithm by introducing a multiple surrogates approach. It means that, for each potential offspring, a surrogate-assisted evolutionary search is conducted in its neighbourhood using the best local surrogate among Kriging, Artificial Neural Networks (ANN) and Radial Basis Function (RBF). This makes the algorithm suitable for time-consuming objective function evaluations, as is often the case in induction heating numerical simulations. We called MSAiTDEA the new algorithm.
AB - We improved iTDEA, an existing preference-based multi-objective evolutionary algorithm by introducing a multiple surrogates approach. It means that, for each potential offspring, a surrogate-assisted evolutionary search is conducted in its neighbourhood using the best local surrogate among Kriging, Artificial Neural Networks (ANN) and Radial Basis Function (RBF). This makes the algorithm suitable for time-consuming objective function evaluations, as is often the case in induction heating numerical simulations. We called MSAiTDEA the new algorithm.
U2 - 10.13140/RG.2.2.29105.22889
DO - 10.13140/RG.2.2.29105.22889
M3 - Other publication
CY - Hannover
ER -