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A hybrid fuzzy group decision support framework for advanced-technology prioritization at NASA

机译:NASA先进技术优先级的混合模糊组决策支持框架

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The prioritization of advanced-technology projects at the National Aeronautic and Space Administration (NASA) is a difficult task. This difficulty is due to the multiple and often conflicting objectives in addition to the inherent technical complexities and valuation uncertainties involved in the assessment process. As such, a systematic and transparent decision support framework is needed to guide the assessment process, shape the decision outcomes and enable confident choices to be made. Methods for solving Multi-Criteria Decision Making (MCDM) problems have been widely used to select a finite number of alternatives generally characterized by multiple conflicting criteria. However, applying these methods is becoming increasingly difficult for technology assessment in the space industry because there are many emerging risks for which information is not available and decisions are made under significant uncertainty. In this paper, we propose a hybrid fuzzy group decision support framework for technology assessment at NASA. The proposed objective framework is comprised of two modules. In the first module, the complicated structure of the assessment criteria and alternatives are represented and evaluated with the Analytic Network Process (ANP). In the second module, the alternative advanced-technology projects are ranked using a customized fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We demonstrate the applicability of the proposed framework through a case study at the Kennedy Space Center.
机译:国家航空航天局(NASA)优先安排先进技术项目是一项艰巨的任务。除了评估过程中固有的技术复杂性和估值不确定性外,这一困难还归因于多重且经常相互冲突的目标。因此,需要一个系统,透明的决策支持框架来指导评估过程,确定决策结果并做出自信的选择。解决多标准决策(MCDM)问题的方法已广泛用于选择通常以多个冲突标准为特征的有限数量的替代方案。但是,由于存在许多无法获得信息并且在重大不确定性下做出决策的新兴风险,因此应用这些方法进行太空工业技术评估变得越来越困难。在本文中,我们提出了一种用于NASA技术评估的混合模糊群体决策支持框架。拟议的目标框架由两个模块组成。在第一个模块中,使用分析网络流程(ANP)表示并评估了评估标准和替代方案的复杂结构。在第二个模块中,使用定制的模糊技术(通过与理想解决方案的相似性来确定优先顺序)对替代的高级技术项目进行排名。我们通过肯尼迪航天中心的案例研究证明了所提出框架的适用性。

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