The Rate-Weight Connected Vectors Processor (RWCVP): A Method for Dealing with Uncertainty in MCDM Problems

Shervin Zakeri, Dimitris Konstantas, R. Bratvold
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Abstract

This paper introduces the rate-weight connected vectors processor (RWCVP) method to address the lack of multi- criteria decision-making (MCDM) methods in handling uncertainty for solving MCDM problems. According to the literature, RWCVP is the only MCDM method that requires no additional methods and models for solving MCDM problems with uncertain data (e.g., fuzzy logic). The new method computes the areas generated between two connected vectors of the alternatives’ rates against the criteria and the criteria weights in order to determine the best alternative. In spite of the fact that RWCVP does not require using the current models and theories, such as fuzzy logic or grey systems theory, for solving the MCDM problems with uncertain data, it still demands a numeric pattern to convert the uncertain information into the numeric values. Hence, we proposed RWCVP: Type I, which utilizes triangular numbers with two upper and lower bounds and a center. The new method was applied to a numeric example and compared with fuzzy TOPSIS and TOPSIS with defuzziefied values. The obtained results revealed that RWCVP: Type I is a reliable MCDM method in dealing with uncertainty and is more transparent than the TOPSIS method.
速率-权重连接向量处理器(RWCVP):一种处理MCDM问题中不确定性的方法
针对多准则决策(MCDM)方法在处理不确定性方面的不足,提出了速率-权重连接向量处理器(RWCVP)方法。根据文献,RWCVP是唯一不需要额外的方法和模型来解决数据不确定(如模糊逻辑)的MCDM问题的MCDM方法。该方法根据标准和标准权重计算两个连通向量之间产生的面积,以确定最佳方案。尽管RWCVP不需要使用现有的模型和理论,如模糊逻辑或灰色系统理论来解决具有不确定数据的MCDM问题,但它仍然需要一个数值模式来将不确定信息转换为数值。因此,我们提出了RWCVP: Type I,它使用具有两个上界和下界和一个中心的三角形数。将新方法应用于一个数值算例,并与模糊TOPSIS和去模糊值TOPSIS进行了比较。结果表明,RWCVP: Type I在处理不确定性方面是一种可靠的MCDM方法,并且比TOPSIS方法更透明。
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