English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Poster

Systematic comparison of flowsheet optimization options: surrogate modelling vs. genetic algorithms vs Bayesian optimization.

MPS-Authors
/persons/resource/persons292887

Ganzer,  Caroline
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

/persons/resource/persons86497

Sundmacher,  Kai       
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Ganzer, C., & Sundmacher, K. (2024). Systematic comparison of flowsheet optimization options: surrogate modelling vs. genetic algorithms vs Bayesian optimization. Poster presented at 34th Eu­ro­pean Sym­po­si­um on Com­pu­ter-Ai­ded Pro­cess En­gi­nee­ring (ES­CAPE-34), Florence, Italy.


Cite as: https://hdl.handle.net/21.11116/0000-000F-FCE8-0
Abstract
There is no abstract available