Title | ||
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An integrated approach to evaluate module partition schemes of complex products and systems based on interval-valued intuitionistic fuzzy sets |
Abstract | ||
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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. |
Year | DOI | Venue |
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2014 | 10.1080/0951192X.2013.834471 | International Journal of Computer Integrated Manufacturing |
Keywords | DocType | Volume |
topsis,module partition schemes evaluation,interval-valued intuitionistic fuzzy cross-entropy,multiple attribute decision-making,interval-valued intuitionistic fuzzy sets | Journal | 27 |
Issue | ISSN | Citations |
7 | 0951-192X | 2 |
PageRank | References | Authors |
0.37 | 32 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Yupeng Li | 1 | 2 | 0.70 |
Xuening Chu | 2 | 238 | 21.29 |
Dexin Chu | 3 | 3 | 1.40 |
Xiuli Geng | 4 | 82 | 4.15 |
Xiaosong Wu | 5 | 2 | 0.37 |