Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP
<i>Background:</i> Dual-level stochastic programming is a technique that allows modelling uncertainty at two different levels, even when the time granularity differs vastly between the levels. In this paper we study the problem of determining the optimal fleet size and mix of vessels per...
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MDPI AG
2022-01-01
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| Series: | Logistics |
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| Online Access: | https://www.mdpi.com/2305-6290/6/1/6 |
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| author | Kamilla Hamre Bolstad Manu Joshi Lars Magnus Hvattum Magnus Stålhane |
| author_facet | Kamilla Hamre Bolstad Manu Joshi Lars Magnus Hvattum Magnus Stålhane |
| author_sort | Kamilla Hamre Bolstad |
| collection | DOAJ |
| description | <i>Background:</i> Dual-level stochastic programming is a technique that allows modelling uncertainty at two different levels, even when the time granularity differs vastly between the levels. In this paper we study the problem of determining the optimal fleet size and mix of vessels performing maintenance operations at offshore wind farms. In this problem the strategic planning spans decades, while operational planning is performed on a day-to-day basis. Since the operational planning level must somehow be taken into account when making strategic plans, and since uncertainty is present at both levels, dual-level stochastic programming is suitable. <i>Methods:</i> We present a heuristic solution method for the problem based on the greedy randomized adaptive search procedure (GRASP). To evaluate the operational costs of a given fleet, a novel fleet deployment heuristic (FDH) is embedded into the GRASP. <i>Results:</i> Computational experiments show that the FDH produces near optimal solutions to the operational day-to-day fleet deployment problem. Comparing the GRASP to exact methods, it produces near optimal solutions for small instances, while significantly improving the primal solutions for larger instances, where the exact methods do not converge. <i>Conclusions:</i> The proposed heuristic is suitable for solving realistic instances, and produces near optimal solution in less than 2 h. |
| format | Article |
| id | doaj-art-1041cf3e6a3c45ef9de43b2bafd233b6 |
| institution | DOAJ |
| issn | 2305-6290 |
| language | English |
| publishDate | 2022-01-01 |
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| series | Logistics |
| spelling | doaj-art-1041cf3e6a3c45ef9de43b2bafd233b62025-08-20T02:44:42ZengMDPI AGLogistics2305-62902022-01-0161610.3390/logistics6010006Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASPKamilla Hamre Bolstad0Manu Joshi1Lars Magnus Hvattum2Magnus Stålhane3Department of Industrial Economics and Technology Management, NTNU, 7491 Trondheim, NorwayDepartment of Industrial Economics and Technology Management, NTNU, 7491 Trondheim, NorwayFaculty of Logistics, Molde University College, 6410 Molde, NorwayDepartment of Industrial Economics and Technology Management, NTNU, 7491 Trondheim, Norway<i>Background:</i> Dual-level stochastic programming is a technique that allows modelling uncertainty at two different levels, even when the time granularity differs vastly between the levels. In this paper we study the problem of determining the optimal fleet size and mix of vessels performing maintenance operations at offshore wind farms. In this problem the strategic planning spans decades, while operational planning is performed on a day-to-day basis. Since the operational planning level must somehow be taken into account when making strategic plans, and since uncertainty is present at both levels, dual-level stochastic programming is suitable. <i>Methods:</i> We present a heuristic solution method for the problem based on the greedy randomized adaptive search procedure (GRASP). To evaluate the operational costs of a given fleet, a novel fleet deployment heuristic (FDH) is embedded into the GRASP. <i>Results:</i> Computational experiments show that the FDH produces near optimal solutions to the operational day-to-day fleet deployment problem. Comparing the GRASP to exact methods, it produces near optimal solutions for small instances, while significantly improving the primal solutions for larger instances, where the exact methods do not converge. <i>Conclusions:</i> The proposed heuristic is suitable for solving realistic instances, and produces near optimal solution in less than 2 h.https://www.mdpi.com/2305-6290/6/1/6heuristicfleet size and mixoffshore winduncertaintymulti-horizon |
| spellingShingle | Kamilla Hamre Bolstad Manu Joshi Lars Magnus Hvattum Magnus Stålhane Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP Logistics heuristic fleet size and mix offshore wind uncertainty multi-horizon |
| title | Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP |
| title_full | Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP |
| title_fullStr | Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP |
| title_full_unstemmed | Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP |
| title_short | Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP |
| title_sort | composing vessel fleets for maintenance at offshore wind farms by solving a dual level stochastic programming problem using grasp |
| topic | heuristic fleet size and mix offshore wind uncertainty multi-horizon |
| url | https://www.mdpi.com/2305-6290/6/1/6 |
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