Imperial College London
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ProfessorRuthMisener

Faculty of Engineering, Department of Computing

Professor in Computational Optimisation
 
 
 
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Contact

 

+44 (0)20 7594 8315r.misener Website CV

 
 
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Location

 

379Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Ceccon:2019:10.1007/s11590-019-01396-y,
author = {Ceccon, F and Siirola, J and Misener, R},
doi = {10.1007/s11590-019-01396-y},
journal = {Optimization Letters},
pages = {801--814},
title = {SUSPECT: MINLP special structure detector for pyomo},
url = {http://dx.doi.org/10.1007/s11590-019-01396-y},
volume = {14},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We present SUSPECT, an open source toolkit that symbolically analyzesmixed-integer  nonlinear  optimization  problems  formulated  using  the  Python  alge-braic modeling library Pyomo. We present the data structures and algorithms used toimplement SUSPECT. SUSPECT works on a directed acyclic graph representation ofthe optimization problem to perform: bounds tightening, bound propagation, mono-tonicity detection, and convexity detection. We show how the tree-walking rules inSUSPECT balance the need for lightweight computation with effective special struc-ture detection. SUSPECT can be used as a standalone tool or as a Python library to beintegrated in other tools or solvers. We highlight the easy extensibility of SUSPECTwith several recent convexity detection tricks from the literature. We also report ex-perimental results on the MINLPLib 2 dataset.
AU  - Ceccon,F
AU  - Siirola,J
AU  - Misener,R
DO  - 10.1007/s11590-019-01396-y
EP  - 814
PY  - 2019///
SN  - 1862-4472
SP  - 801
TI  - SUSPECT: MINLP special structure detector for pyomo
T2  - Optimization Letters
UR  - http://dx.doi.org/10.1007/s11590-019-01396-y
UR  - https://link.springer.com/article/10.1007%2Fs11590-019-01396-y
UR  - http://hdl.handle.net/10044/1/67234
VL  - 14
ER  -
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