EAHVFA - A Surrogate-Assisted Evolutionary Algorithm with Hypervolume Triggered Fidelity Adjustment for Noisy Multiobjective Integer Programming
------------------------------- Reference --------------------------------
Liu S, Wang H, Yao W. A Surrogate-Assisted Evolutionary Algorithm with Hypervolume Triggered Fidelity Adjustment for Noisy Multiobjective Integer Programming in Applied Soft Computing. 2022.
------------------------------- Copyright --------------------------------
Copyright (c) HandingWangXDGroup. Permission is granted to copy and use this code for research, noncommercial purposes, provided this copyright notice is retained and the origin of the code is cited. The code is provided "as is" and without any warranties, express or implied.
Email: shuleiliu@126.com
- DEAP
- hvwfg
- pymoo
- scikit-learn
The example code of runing EAHVFA algorithm is shown in the examples folder.