Imperial College London

ProfessorRuthMisener

Faculty of EngineeringDepartment 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{Baltean-Lugojan and Misener:2018:10.1007/s10898-017-0577-y,
author = {Baltean-Lugojan and Misener, R},
doi = {10.1007/s10898-017-0577-y},
journal = {Journal of Global Optimization},
pages = {655--690},
title = {Piecewise parametric structure in the pooling problem - from sparse, strongly-polynomial solutions to NP-hardness},
url = {http://dx.doi.org/10.1007/s10898-017-0577-y},
volume = {71},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The standard pooling problem is a NP-hard subclass of non-convex quadratically-constrained optimization problems that commonly arises in process systems engineering applications. We take a parametric approach to uncovering topological structure and sparsity, focusing on the single quality standard pooling problem in its p-formulation. The structure uncovered in this approach validates Professor Christodoulos A. Floudas’ intuition that pooling problems are rooted in piecewise-defined functions. We introduce dominant active topologies under relaxed flow availability to explicitly identify pooling problem sparsity and show that the sparse patterns of active topological structure are associated with a piecewise objective function. Finally, the paper explains the conditions under which sparsity vanishes and where the combinatorial complexity emerges to cross over the P / NP boundary. We formally present the results obtained and their derivations for various specialized single quality pooling problem subclasses.
AU - Baltean-Lugojan
AU - Misener,R
DO - 10.1007/s10898-017-0577-y
EP - 690
PY - 2018///
SN - 0925-5001
SP - 655
TI - Piecewise parametric structure in the pooling problem - from sparse, strongly-polynomial solutions to NP-hardness
T2 - Journal of Global Optimization
UR - http://dx.doi.org/10.1007/s10898-017-0577-y
UR - http://hdl.handle.net/10044/1/51655
VL - 71
ER -