针对第三方逆向物流供应商评价过程中的指标冗余、指标权重的确定需要直接赋权和信息不确定性等问题,提出一种基于粗糙集的灰色TOPSIS法,使评价结果更加科学合理。首先,根据粗糙集的约简理论对构建的初步指标体系进行约简;其次利用粗糙集理论,根据系统自身属性的重要性度量确定指标的权重;并且采用灰色理论中的灰数对不确定信息进行度量,建立TOPSIS中的规范矩阵。以此对第三方逆向物流供应商进行综合评价。最后以对10个第三方逆向物流供应商的评价为例验证该方法的有效性。
Three issues of indicators redundancy, indicators weights in need of direct empowerment and information uncertainty need to be addressed in the decision making process of the third party reverse logistic vendor selection. A rough set - based grey -Topsis approach is proposed to make assessment more rationally. Firstly, a rough set reduction theory is used to reduce the number of the original indicators. The rough set theory is then applied to determine the weights of indicators based on the attribute of indicators system itself. Further, the grey theory is presented to measure the uncertain information, by the establishment of normal matrix in Topsis. Finally, an illustrative example of evaluation analysis for ten third party re- verse logistic vendors is put forward to demonstrate the efficacy of the approach.