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@inbook{Wiebe:2021:10.1016/B978-0-323-88506-5.50108-X,
author = {Wiebe, J and Misener, R},
booktitle = {Computer Aided Chemical Engineering},
doi = {10.1016/B978-0-323-88506-5.50108-X},
pages = {683--688},
title = {ROmodel: A Python Robust Optimization Modeling Toolbox},
url = {http://dx.doi.org/10.1016/B978-0-323-88506-5.50108-X},
year = {2021}
}

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TY  - CHAP
AB  - We introduce ROmodel, a Python package that extends the modeling capabilities of the popular modeling language Pyomo to robust optimization problems. ROmodel contains a library of commonly used uncertainty sets which can be generated using their matrix representations, but it also allows the definition of custom uncertainty sets using Pyomo constraints. The resulting models can be solved using ROmodels solvers which implement both the robust reformulation and cutting plane approach. We apply the problem to a number of instances of three case studies and show some results.
AU  - Wiebe,J
AU  - Misener,R
DO  - 10.1016/B978-0-323-88506-5.50108-X
EP  - 688
PY  - 2021///
SP  - 683
TI  - ROmodel: A Python Robust Optimization Modeling Toolbox
T1  - Computer Aided Chemical Engineering
UR  - http://dx.doi.org/10.1016/B978-0-323-88506-5.50108-X
ER  -

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