Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance

© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Abstract: Emissions can be reduced through the implementation of various combinations of control or prevention measures, or combinations thereof. However, the total cost and performance of such emissions reduction measures can often be d...

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Main Authors: Aviso, Kathleen B., Ngo, Janne Pauline S., Sy, Charlle L., Tan, Raymond Girard R.
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Published: Animo Repository 2019
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1091
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2090/type/native/viewcontent
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-20902022-07-05T02:55:12Z Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance Aviso, Kathleen B. Ngo, Janne Pauline S. Sy, Charlle L. Tan, Raymond Girard R. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Abstract: Emissions can be reduced through the implementation of various combinations of control or prevention measures, or combinations thereof. However, the total cost and performance of such emissions reduction measures can often be difficult to predict precisely. Such uncertainties result in techno-economic risks that firms will have to deal with when implementing a project aimed at cutting emissions. In this work, an integer linear programming model is extended using the target-oriented robust optimization (TORO) framework for determining the best mix of emissions reduction measures. This framework allows optimization to be carried out with uncertain model parameters given in the form of intervals. A range of potential solutions can then be generated and subjected to Monte Carlo simulation to gauge their robustness. The decision maker can select a solution to implement based on the information regarding the expected performance, cost and robustness of the mix of emissions reduction measures. Case studies on reduction of hydrogen fluoride emissions from brick manufacturing and CO2 emissions from maritime vessels are solved to illustrate the methodology. The examples demonstrate the capability of the TORO model to identify good solutions that are able to perform well despite variations in techno-economic conditions. Graphical abstract: [Figure not available: see fulltext.] 2019-01-15T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/1091 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2090/type/native/viewcontent Faculty Research Work Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
description © 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Abstract: Emissions can be reduced through the implementation of various combinations of control or prevention measures, or combinations thereof. However, the total cost and performance of such emissions reduction measures can often be difficult to predict precisely. Such uncertainties result in techno-economic risks that firms will have to deal with when implementing a project aimed at cutting emissions. In this work, an integer linear programming model is extended using the target-oriented robust optimization (TORO) framework for determining the best mix of emissions reduction measures. This framework allows optimization to be carried out with uncertain model parameters given in the form of intervals. A range of potential solutions can then be generated and subjected to Monte Carlo simulation to gauge their robustness. The decision maker can select a solution to implement based on the information regarding the expected performance, cost and robustness of the mix of emissions reduction measures. Case studies on reduction of hydrogen fluoride emissions from brick manufacturing and CO2 emissions from maritime vessels are solved to illustrate the methodology. The examples demonstrate the capability of the TORO model to identify good solutions that are able to perform well despite variations in techno-economic conditions. Graphical abstract: [Figure not available: see fulltext.]
format text
author Aviso, Kathleen B.
Ngo, Janne Pauline S.
Sy, Charlle L.
Tan, Raymond Girard R.
spellingShingle Aviso, Kathleen B.
Ngo, Janne Pauline S.
Sy, Charlle L.
Tan, Raymond Girard R.
Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
author_facet Aviso, Kathleen B.
Ngo, Janne Pauline S.
Sy, Charlle L.
Tan, Raymond Girard R.
author_sort Aviso, Kathleen B.
title Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
title_short Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
title_full Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
title_fullStr Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
title_full_unstemmed Target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
title_sort target-oriented robust optimization of emissions reduction measures with uncertain cost and performance
publisher Animo Repository
publishDate 2019
url https://animorepository.dlsu.edu.ph/faculty_research/1091
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2090/type/native/viewcontent
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