Today, most institutions and companies delegate reverse logistics services, organizational communication, and outsourcing company to a third-party logistics reverse provider. To select an appropriate third-party logistics provider, this study proposes a decision-making procedure considering dual role data and fuzzy states based on data envelopment analysis models. After determining evaluation indices, this study uses the $\alpha$-cut approach to transform the proposed model under uncertainty to a deterministic model. Finally, a case study (collection and burial of hospital waste) is presented to show the application of this research. Results of selecting the best third-party logistics provider and more analyses are provided after coding in GAMS software.

今天，大多数机构和公司将逆向物流服务、组织沟通和外包公司委托给第三方物流逆向供应商。为了选择合适的第三方物流供应商，本研究基于数据包络分析模型提出了一种考虑双重角色数据和模糊状态的决策程序。在确定评价指标后，本研究采用$\alpha$-cut 方法将不确定性下的建议模型转换为确定性模型。最后，通过一个案例研究（医院垃圾的收集和掩埋）来展示这项研究的应用。在 GAMS 软件中编码后提供选择最佳第三方物流供应商的结果和更多分析。