Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families.
- DOI
- 10.1021/acs.iecr.4c03913
- Published
- 2025 Apr 23
- Container
- Industrial & engineering chemistry research
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1021/acs.iecr.4c03913,
title = {Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families.},
author = {Stinchfield G and Khalife N and Ammari BL and Morgan JC and Zamarripa M and Laird CD},
year = {2025},
journal = {Industrial \& engineering chemistry research},
doi = {10.1021/acs.iecr.4c03913},
url = {https://doi.org/10.1021/acs.iecr.4c03913}
}RIS
TY - JOUR TI - Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families. AU - Stinchfield G AU - Khalife N AU - Ammari BL AU - Morgan JC AU - Zamarripa M AU - Laird CD PY - 2025 JO - Industrial & engineering chemistry research DO - 10.1021/acs.iecr.4c03913 UR - https://doi.org/10.1021/acs.iecr.4c03913 ER -
APA
G, S., N, K., BL, A., JC, M., M, Z., & CD, L. (2025). Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families.. Industrial & engineering chemistry research. https://doi.org/10.1021/acs.iecr.4c03913
Source records
- pubmed · retrieved 2026-09-27T08:15:35.268Z
- europe-pmc · retrieved 2026-09-27T08:15:35.279Z