A robust optimization approach to locating and stockpiling marine oil-spill response facilities
In this research, a robust optimization approach is proposed to the problem of designing emergency response networks for marine oil-spills given uncertainty in the location, size and type of the spill. In this regard, we formulate two robust models (Gamma and Ellipsoidal) to optimize the allocation...
Main Authors: | , , |
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Format: | Article in Journal/Newspaper |
Language: | unknown |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1366554520306566 |
_version_ | 1821624939938054144 |
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author | Sarhadi, Hassan Naoum-Sawaya, Joe Verma, Manish |
author_facet | Sarhadi, Hassan Naoum-Sawaya, Joe Verma, Manish |
author_sort | Sarhadi, Hassan |
collection | RePEc (Research Papers in Economics) |
description | In this research, a robust optimization approach is proposed to the problem of designing emergency response networks for marine oil-spills given uncertainty in the location, size and type of the spill. In this regard, we formulate two robust models (Gamma and Ellipsoidal) to optimize the allocation of response equipment while considering the underlying uncertainty in each oil-spill scenario. An efficient Branch-and-Cut algorithm is then designed to improve the computational performance. The benefits of applying the robust formulations are illustrated and compared to the non-robust model using a realistic case study from Newfoundland (Canada). Marine oil-spill; Emergency response; Robust optimization; Mixed-integer program; Stochasticity; |
format | Article in Journal/Newspaper |
genre | Newfoundland |
genre_facet | Newfoundland |
geographic | Canada |
geographic_facet | Canada |
id | ftrepec:oai:RePEc:eee:transe:v:141:y:2020:i:c:s1366554520306566 |
institution | Open Polar |
language | unknown |
op_collection_id | ftrepec |
op_relation | http://www.sciencedirect.com/science/article/pii/S1366554520306566 |
record_format | openpolar |
spelling | ftrepec:oai:RePEc:eee:transe:v:141:y:2020:i:c:s1366554520306566 2025-01-16T23:23:52+00:00 A robust optimization approach to locating and stockpiling marine oil-spill response facilities Sarhadi, Hassan Naoum-Sawaya, Joe Verma, Manish http://www.sciencedirect.com/science/article/pii/S1366554520306566 unknown http://www.sciencedirect.com/science/article/pii/S1366554520306566 article ftrepec 2024-03-19T10:36:29Z In this research, a robust optimization approach is proposed to the problem of designing emergency response networks for marine oil-spills given uncertainty in the location, size and type of the spill. In this regard, we formulate two robust models (Gamma and Ellipsoidal) to optimize the allocation of response equipment while considering the underlying uncertainty in each oil-spill scenario. An efficient Branch-and-Cut algorithm is then designed to improve the computational performance. The benefits of applying the robust formulations are illustrated and compared to the non-robust model using a realistic case study from Newfoundland (Canada). Marine oil-spill; Emergency response; Robust optimization; Mixed-integer program; Stochasticity; Article in Journal/Newspaper Newfoundland RePEc (Research Papers in Economics) Canada |
spellingShingle | Sarhadi, Hassan Naoum-Sawaya, Joe Verma, Manish A robust optimization approach to locating and stockpiling marine oil-spill response facilities |
title | A robust optimization approach to locating and stockpiling marine oil-spill response facilities |
title_full | A robust optimization approach to locating and stockpiling marine oil-spill response facilities |
title_fullStr | A robust optimization approach to locating and stockpiling marine oil-spill response facilities |
title_full_unstemmed | A robust optimization approach to locating and stockpiling marine oil-spill response facilities |
title_short | A robust optimization approach to locating and stockpiling marine oil-spill response facilities |
title_sort | robust optimization approach to locating and stockpiling marine oil-spill response facilities |
url | http://www.sciencedirect.com/science/article/pii/S1366554520306566 |