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Simulation screening experiments using Lasso-optimal supersaturated design and analysis: A maritime operations application

机译:使用套索最优过饱和设计和分析模拟筛选实验:海事运营应用

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Screening methods are beneficial for studies involving simulations that have a large number of variables where a relatively small (but unknown) subset is important. In this paper, we show how a newly proposed Lasso-optimal screening design and analysis method can be useful for efficiently conducting simulation screening experiments. Our approach uses new criteria for generating supersaturated designs, and a new algorithm for selecting the optimal tuning parameters for Lasso model selection. We generate a 24×69 Lasso optimal supersaturated design, illustrate its potential with a numerical evaluation, and apply it to an agent-based simulation of maritime escort operations in the Strait of Gibraltar. This application is part of a larger project that seeks to leverage simulation models during the ship design process, and so construct ships that are both cost effective and operationally effective. The supersaturated screening design has already proved beneficial for model verification and validation.
机译:筛选方法有利于涉及具有大量变量的模拟的研究,其中相对较小(但未知)子集是重要的。在本文中,我们展示了新提出的套索最优筛选设计和分析方法如何有助于有效地进行仿真筛选实验。我们的方法使用用于生成超饱和设计的新标准,以及用于选择Lasso模型选择的最佳调谐参数的新算法。我们生成24×69套索最优超饱和设计,说明其具有数值评估的潜力,并将其应用于直布罗陀海峡海岸的基于代理的仿真仿真。此应用程序是较大项目的一部分,该部分寻求在船舶设计过程中利用仿真模型,因此构建成本效益和操作性有效的船舶。过饱和的筛选设计已经证明有利于模型验证和验证。

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