Improved hierarchical surrogate-assisted evolutionary algorithm with multiscale variable-reduction strategy for large-sclae optimization
| Main Author: | Cong Xiao |
|---|---|
| Format: | info software Journal |
| Terbitan: |
, 2021
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4656961 |
Daftar Isi:
- This paper proposes a novel hierarchical surrogate-assisted evolutionary algorithm based on multiscale variable-reduction strategy for application to the large-scale production optimization step of closed-loop reservoir management where the objective function is the net present value (NPV) of production from a given reservoir. In addition, well-controls are regularized as well using function control method (FCM) and interpolation control method (ICM) in the literature to make evolutionary algorithm much more well-poised and efficient. We also define a transformation functions, e.g., sigmoid function, to make the well control constrains automatically satisfied and therefore ease the implementation of entire optimization framework.