Abstract
Background: 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. Methods: 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. Results: 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. Conclusions: The proposed heuristic is suitable for solving realistic instances, and produces near optimal solution in less than 2 h.
Highlights
This work is motivated by solving a maritime fleet size and mix problem (MFSMP)
The particular MFSMP studied was presented by Stålhane et al [1], who referred to it as the dual-level fleet size and mix problem for conducting maintenance at offshore wind farms (DLPOW)
Until the paper of Stålhane et al [1], the only paper published on MFSMPs for supporting maintenance activities at offshore wind farms that included long-term uncertainty is that of Gundegjerde et al [3]
Summary
Arising when planning the maintenance of turbines in offshore wind farms. Maintenance tasks must be performed both to reduce the risk of turbine failures and to repair turbines following a breakdown. To evaluate fleet composition decisions, one must consider operational decisions, which are made on a day-to-day basis, regarding which maintenance tasks to perform, and which vessels to use to support each maintenance task As both strategic and operational decisions are influenced by uncertainty, the DLPOW was modelled as a dual-level stochastic problem. Until the paper of Stålhane et al [1], the only paper published on MFSMPs for supporting maintenance activities at offshore wind farms that included long-term uncertainty is that of Gundegjerde et al [3] They proposed a three-stage stochastic program that considered uncertainty in vessel spot rates, electricity prices, weather conditions, and the failure rates of wind turbines.
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