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首页> 外文期刊>International journal of fuzzy system applications >Improving the Computational Process for Identifying Optimal Design Using Fuzzified Decision Models
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Improving the Computational Process for Identifying Optimal Design Using Fuzzified Decision Models

机译:改进使用模糊决策模型识别最优设计的计算过程

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Concept selection in design is an important aspect of design process that must be done properly with the right tools. The identification of optimal design is presented in this article by integrating three multicriteria decision-making models which are fuzzified pairwise comparison matrices, fuzzified weighted decision matrix, and fuzzy VIKOR. Rather than depending solely on design expert's view to determine weights of the design features, the pairwise comparison matrices determines the weights of design features and sub features in the decision process. The weighted decision matrix aggregates scores for the alternative designs considering the availability of sub-features in them. The aggregated scores form the elements of the main decision matrix together with the weights of the design features and the Fuzzy VIKOR model determines the performance index of the design concepts. The hybridized model was validated using four conceptual designs of liquid spraying machines and the results obtained show that the model provides computational integrity in the decision-making process.
机译:设计中的概念选择是设计过程的一个重要方面,必须使用正确的工具正确完成。本文通过整合模糊成对比较矩阵、模糊加权决策矩阵和模糊VIKOR三种多准则决策模型,提出了最优设计的识别。成对比较矩阵不是仅仅依靠设计专家的观点来确定设计特征的权重,而是确定决策过程中设计特征和子特征的权重。加权决策矩阵汇总了备选设计的分数,并考虑了其中子特征的可用性。汇总的分数与设计特征的权重一起构成了主决策矩阵的要素,模糊VICOR模型决定了设计概念的性能指标。使用四种液体喷涂机概念设计对混合模型进行了验证,结果表明该模型在决策过程中提供了计算完整性。

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