TY  - INPR
ID  - SisLab3251
UR  - http://www.cefc2018.org/system/Web/ueditor/asp/upload/file/20181008/15389866299155943.pdf
A1  - Bin, Xia
A1  - Pham, Minh Trien
A1  - Zhang, Yanli
A1  - Koh, Chang Seop
Y1  - 2018/10/28/
N2  - A multi-objective global optimization strategy is de- veloped by incorporating an adaptive dynamic Taylor Kriging (ADTK) into an improved multi-objective differential evolution algorithm (MODE) to achieve a numerically efficient multi- objective optimization algorithm. The basis functions of the ADTK are optimally, adaptively and dynamically selected so that the Kriging model may have better accuracy than any other Kriging model, and the MODE has an improved mutation algo- rithm.
TI  - Utilizing Adaptive Dynamic Taylor Kriging Assisted Multi-Objective DE Algorithm for Optimization Design of Electromagnetic Device
M2  - Hangzhou, China
AV  - public
T2  - 2018 the Eighteenth Biennial IEEE Conference on Electromagnetic Field Computation (CEFC 2018)
ER  -