This is the MATLAB implementation of the incremental Kriging-assisted evolutionary algorithm proposed in [1].
It uses an incremental learning method to update the Kriging model when new samples become available. Therefore, the surrogate modelling process is significantly faster than the traditional learning method.
I referred some MATLAB codes in [2] when coding the incremental Kriging model.
Reference
Dawei Zhan and Huanlai Xing. A Fast Kriging-Assisted Evolutionary Algorithm Based on Incremental Learning. IEEE Transactions on Evolutionary Computation, 2021, 25(5): 941-955.
A. I. J. Forrester, A. Sobester and A. J. Keane. Engineering design via surrogate modelling: a practical guide, 2008, John Wiley & Sons.
incremental_kriging_assisted_evolutionary_algorithm's People
Firstly, thank you for all the help I've received from your paper and source code.
And when I'm training with my own dataset, I don't know how to set the upper and lower bounds of theta and the initial value to get a valid theta value.
I have come across the following conditions:
theta value is a set upper or lower bound;
theta value is a set initial value.
How should I set this? Looking forward and thank you very much for your reply.Best regards.
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