基于云模型的改进TODIM方案评价方法

针对传统方案评价方法只考虑评价信息的模糊性而忽略信息随机性的问题,同时考虑决策者具有参照依赖和损失规避行为,提出基于云模型的改进交互式多属性决策(简称为TODIM)方案评价方法。首先采用云模型对语义评价变量进行量化;其次定义算术平均云,基于云距离测度算法分析专家评价云与算术平均云的相似度,确定专家动态权重,并通过云的集成方法构建加权云决策矩阵;再定义正、负理想云模型并以最大化所有方案的总体贴近度为目标,建立线性规划模型确定指标权重;最后采用基于云距离测度算法的云-TODIM方法计算每个方案相对于其他所有方案的总体优势度,从而对方案排序。以云服务供应商的评价与选择为例,验证了所提方法的有效性。

Improved TODIM approach for alternative evaluation based on cloud model

To overcome the drawback of traditional alternative evaluation approaches, which only considered the fuzziness of evaluation information without considering the randomness of the information, an improved interactive multi-attribute decision making (TODIM) approach based on cloud model is proposed, in which the reference dependence and loss aversion behaviors of the decision maker are considered. Firstly, the cloud model is used to quantize the linguistic evaluation variable. Secondly, arithmetic mean cloud is defined. The dynamic weights of experts are determined by analyzing the similarity between the given expert evaluation cloud and the arithmetic mean cloud, based on the distance measure about the cloud model. Besides, the weighted decision matrix is constructed by integrating the cloud models of experts. Thirdly, the positive and negative ideal cloud models are defined. To maximize the overall closeness degree for all of the alternatives, a linear programming model is established to determine the criteria weights. Finally, the cloud-TODIM method based on the distance measure about the cloud model is used to calculate the overall dominance degree of each alternative relative to all others and obtain the ranking result of alternatives. A case study of cloud service providers evaluation and selection is presented to illustrate the effectiveness of the proposed approach.