A Numerically Efficient Multi-Objective Optimization Algorithm: Combination of Dynamic Taylor Kriging and Differential Evolution

A dynamic Taylor Kriging (DTK) is newly developed and combined with a multi-objective differential evolution algorithm to get a numerically efficient multi-objective optimization strategy. In the DTK, basis functions are not predefined but optimally selected so that the fitting error with the given...

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Veröffentlicht in:	IEEE transactions on magnetics Jg. 51; H. 3; S. 1 - 4
Hauptverfasser:	Bin Xia, Baatar, Nyambayar, Ziyan Ren, Chang-Seop Koh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithm design and analysis Algorithms Dynamics Evolution Fittings Heuristic algorithms Kriging Linear programming Magnetism Mathematical analysis Optimization Prediction algorithms Sampling Sociology Strategy dynamic Taylor Kriging (DTK) Binary particle swarm optimization (B-PSO) multi-objective differential evolution (MODE)
ISSN:	0018-9464, 1941-0069
Online-Zugang:	Volltext
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