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A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

机译:用于在海上风电场安装中支持后勤决策的混合方法优化和仿真框架

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Highlights?A mixed method approach supports decision making for offshore wind farm installation.?An optimisation tool identifies the optimal sequencing of installation operations.?A simulation tool identifies robust start-dates with respect to seasonality.?A case study installation is investigated to demonstrate this mixed method approach.AbstractWith a typical investment in excess of £100 million for each project, the installation phase of offshore wind farms (OWFs) 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 a
机译:<![CDATA [ 亮点 一种混合方法方法支持决策对于海上风力发电场安装 的优化工具识别的最佳测序安装操作的 “所有” 一种模拟工具识别鲁棒起动日期相对于季节性 为例安装进行了研究以证明该混合方法的方法 < / CE:抽象秒> 抽象 随着过量为每个项目,海上风电场的安装阶段的典型的投资£亿( OWFs)是其中显着的成本降低,可以实现的区域;然而,最新出现了相对较少的研究探讨这个。在本文中,我们开发了一个混合方法框架,它利用了两个决策支持方法的优势互补:离散事件仿真和鲁棒优化。模拟组件允许开发者来估计用户定义一个的影响

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