BibTex format
@unpublished{Wiebe:2021,
author = {Wiebe, J and Misener, R},
publisher = {arXiv},
title = {ROmodel: Modeling robust optimization problems in Pyomo},
url = {http://arxiv.org/abs/2105.08598v1},
year = {2021}
}
Publications
Citation
RIS format (EndNote, RefMan)
TY - UNPB
AB - This paper introduces ROmodel, an open source Python package extending themodeling capabilities of the algebraic modeling language Pyomo to robustoptimization problems. ROmodel helps practitioners transition fromdeterministic to robust optimization through modeling objects which allowformulating robust models in close analogy to their mathematical formulation.ROmodel contains a library of commonly used uncertainty sets which can begenerated using their matrix representations, but it also allows users todefine custom uncertainty sets using Pyomo constraints. ROmodel supportsadjustable variables via linear decision rules. The resulting models can besolved using ROmodels solvers which implement both the robust reformulation andcutting plane approach. ROmodel is a platform to implement and compare customuncertainty sets and reformulations. We demonstrate ROmodel's capabilities byapplying it to six case studies. We implement custom uncertainty sets based on(warped) Gaussian processes to show how ROmodel can integrate data-drivenmodels with optimization.
AU - Wiebe,J
AU - Misener,R
PB - arXiv
PY - 2021///
TI - ROmodel: Modeling robust optimization problems in Pyomo
UR - http://arxiv.org/abs/2105.08598v1
UR - http://hdl.handle.net/10044/1/88920
ER -