Silvente, J;
Papageorgiou, LG;
Dua, V;
(2019)
Scenario tree reduction for optimisation under uncertainty using sensitivity analysis.
Computers and Chemical Engineering
, 125
pp. 449-459.
10.1016/j.compchemeng.2019.03.043.
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Abstract
This work addresses the optimal management of a system through a two-stage stochastic Non-Linear Programming (NLP) formulation. This approach uses a scenario-based mathematical formulation to tackle uncertain information. Accurate representation of uncertainty usually involves increased number of scenarios, which may result in large-scale optimisation models. Thus, the proposed formulation aims to reduce the number of scenarios through a sensitivity analysis approach. The proposed model investigates the use of scenario reduction techniques to reduce computational requirements while maintaining good quality of the final optimal solution.
| Type: | Article |
|---|---|
| Title: | Scenario tree reduction for optimisation under uncertainty using sensitivity analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.compchemeng.2019.03.043 |
| Publisher version: | http://doi.org/10.1016/j.compchemeng.2019.03.043 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Uncertainty, NLP, Scenario reduction, sensitivity analysis, optimisation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10072980 |
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