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An integrated approach to evaluate module partition schemes of complex products and systems based on interval-valued intuitionistic fuzzy sets

机译：基于区间值直觉模糊集的复杂产品和系统模块划分方案评估的集成方法

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摘要

Modularisation strategy can effectively shorten the lead time and reduce the cost of complex products and systems (CoPS) development. A few schemes are usually obtained through module partition because of the multidimensional complexity of CoPS. Unfortunately, research has rarely been conducted on the module partition schemes evaluation (MPSE) that is a complicated multiple attribute decision-making (MADM) problem under fuzzy and uncertain environment. The interval-valued intuitionistic fuzzy set (IVIFS) theory has distinct advantage on dealing with the imprecise and uncertain information in decision-making. In this article, an integrated MPSE approach is developed based on IVIFS. First, the evaluation measures are provided in the form of interval-valued intuitionistic fuzzy numbers (IVIFNs). Then the aggregation operators of IVIFSs utilised to construct the fuzzy synthetic decision matrix (FSDM) are obtained based on Karnik-Mendel algorithms. Finally, the interval-valued intuitionistic fuzzy (IVIF) cross-entropy integrated with the TOPSIS framework is developed to rank the candidate alternatives. The MPSE methods have been used to the design of a large tonnage crawler crane to illustrate that proposed approach is effective and systematic to solve the MPSE problem of CoPS.
机译：模块化策略可以有效缩短交付周期并降低复杂产品和系统（CoPS）开发的成本。由于CoPS的多维复杂性，通常可以通过模块划分获得一些方案。不幸的是，很少对模块划分方案评估（MPSE）进行研究，该模块划分方案评估是在模糊和不确定环境下的复杂多属性决策（MADM）问题。区间值直觉模糊集（IVIFS）理论在处理决策中不精确和不确定的信息方面具有明显的优势。在本文中，基于IVIFS开发了一种集成的MPSE方法。首先，以区间值直觉模糊数（IVIFN）的形式提供评估措施。然后，基于Karnik-Mendel算法，获得了用于构建模糊综合决策矩阵（FSDM）的IVIFS的聚合算子。最后，开发了与TOPSIS框架集成的区间值直觉模糊（IVIF）交叉熵来对候选替代方案进行排名。 MPSE方法已被用于大吨位履带起重机的设计中，以说明所提出的方法对于解决CoPS的MPSE问题是有效且系统的。

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