## 4 Discussion
### Future Work  
Future work on this approach will focus on the extension of the underlying model to incorporate additional restrictions, e.g., port-side capacity requirements, component deliveries, and componentproduction times. Moreover, this article assumes that personnel is always available. In practice, planners try to ensure this availability by assigning a sufficient number of crews to each vessel. A more dedicated planning of personnel could, on the one hand, result in even more efficient plans by avoiding over-staffing, while it, on the other hand, will impose additional constraints. Therefore, offshore personnel require specific training, especially during the commissioning of wind turbines. Consequently, future work will consider the integration of staff planning tasks. In the context of expanding the model, future work will also focus on the identification of realistic model parameters, e.g., for the cost of operations. Currently, this article only applies assumptions, especially for the costs and benefits applied by the MILP model.  
The current implementation does not make use of the MPC's terminal cost function. This function applies costs after the complete open loop finished and, thereby, allows inclusion of costs that cannot be directly allocated to single planning steps. Future work will investigate how to incorporate this terminal cost function in the current approach, e.g., to regard general charter rates for resources over the complete plan. This incorporation could allow enforcement of lower project durations on the overall plan and not only on planning segments. Finally, future work will provide a comparison between this approach and classic robust and stochastic scheduling approaches to provide a quantitative evaluation of its performance against the state of the art.  
Another topic for future work is the integration with current systems for the planning and monitoring of offshore activities. While this article focuses on the development of suitable methods and models for the actual planning, a real-world decision-support system requires interoperability with existing systems to obtain the required feedbacks and pass the generated plans. Future work will accordingly deal with the investigation of exiting tools and practices in this area. Methods from Dynamic Data Driven Application Systems (DDDAS) [41] will be evaluated to enable an integration. These methods follow a similar scheme as the MPC-based approach presented in this article and, thus, might prove suitable for this task.  
This article briefly lists the individual contributions of the authors: conceptualization, D.R.; methodology, D.R. and N.J.; software, D.R. and N.J.; writing--original draft preparation, D.R. and N.J.; writing--review and editing, M.L. and M.F.; visualization, D.R.; supervision, M.L. and M.F.; project administration, M.L.; funding acquisition, M.L. and D.R.  
This research was funded by the German Research Foundation (DFG) for the research project \"OffshorePlan-Complementary application of mathematical and discrete-event models to solve complex planning and control problems in offshore construction logistics.\" grant number LU 2049/1-1. The APC was funded by the Staats und Universitatsbilothek Bremen.  
The authors declare no conflict of interest.