基于熵权迭代的区域物流多属性模糊群决策评估模型

Multi-attribute Fuzzy Group Decision Model for Regional Logistics Evaluation Based on Entropy Weight Iteration

为了快速、便捷地对区域物流水平进行评估,提出一种多属性群决策评估模型。设立自然语意变量集,建立自然语意变量与梯形模糊数的对应关系,构建包含顶层指标、3个中间层指标、12个底层指标的三级评估指标体系。基于群体熵最小化原则,通过循环修正计算得到用于指标重要性判断的专家权重和对评估区域进行评定的专家权重,通过确定底层指标、中间层指标的相对指标权重,依次计算评估对象在底层指标、中间层指标、顶层指标的评定值,并根据评估对象在顶层指标的评定值确定评估对象的可能度矩阵及排序向量,最后基于排序值对评估对象的区域物流水平进行排序,通过评估还有助于找出评估对象的相对优势及不足。算例研究验证了评估模型的可行性和有效性。

In order to evaluate the regional logistics level quickly and conveniently,a multi-attribute group decision evaluation model is designed.A set of natural semantic variables is established,and the corresponding relationship between natural semantic variables and trapezoidal fuzzy numbers is instituted.A three-level evaluation index system is constructed including top-level indicator,three intermediate-level indicators,and 12 bottom-level indicators.Based on the principle of population entropy minimizing,the expert weights of expert judging indicators'importance and the expert weights of experts'assessment on evaluation objects are obtained through cyclic modificatory calculation.The relative index weights of the bottom-level indicators and the intermediate-level indicators are calculated,and the assessment values of the evaluation objects in the bottom-level indicators,the intermediate-level indicators,and the top-level indicator are calculated in turn.According to the assessment value of the evaluation object in the top-level indicator,the likelihood matrix and the sorting vector of the evaluation object are obtained,and the regional logistics level of the evaluation object is sorted based on the sorting value.The assessment also helps to identify the relative strengths and weaknesses of the evaluation objects.The case study verifies the feasibility and effectiveness of the evaluation model.