For offshore wind to be competitive with mature energy industries, cost efficiencies must be improved throughout the lifetime of an offshore wind farm (OWF). With expensive equipment hire spanning several years, installation is an area where large savings can potentially be made. Installation operations are subject to uncertain weather conditions, with more extreme conditions as OWF developments tend towards larger sites, further offshore in deeper waters. One approach to reduce the cost of the installation process is to evaluate advanced technologies or operational practices. However, in order to demonstrate cost savings, the impact of these advances on the installation process must be quantified in the presence of uncertain environmental conditions. To addresses this challenge a simulation tool is developed to model the logistics of the installation process and to identify the vessels and operations most sensitive to weather delays. These operations are explored to identify the impact of technological or operational advances with respect to weather delays and the resulting installation duration under different levels of weather severity. The tool identifies that loading operations contribute significantly to the overall delay of the installation process, and that a non-linear relationship exists between vessel operational limits and the duration of installation

The problem of finding a strict total order for a finite set of multiple criteria alternatives is considered. Our research extends previous work by us, which considered finding a partial order for a finite set of alternatives. We merge the preference information extracted from the preference cones and corresponding polyhedral sets, with the information derived from pairwise comparisons of two alternatives, yielding a preference matrix. This preference matrix is used as input to an integer programming model to obtain a strict total order that provides a transitive ranking for the set of alternatives. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 155–163, 2014

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With a typical investment of in excess of £100 million for each project, the installation phase of offshore wind farms is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined tool, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities