A New Decision Framework of Online Multi-Attribute Reverse Auctions for Green Supplier Selection under Mixed Uncertainty

In order to realize the “dual carbon” goal proposed for world and seek low-carbon sustainable development of economy society, green supply chain management problem faced by Chinese enterprises governments is particularly important. At same time, how quickly efficiently select suitable supplier most basic critical link in management, as well an important issue that government must face process material procurement. addition, there are various uncertainties emerging current market environment hinder suppliers buyer make efficient decisions. Therefore, find a more method selection, from standpoint buyer, new decision framework online multi-sourcing, multi-attribute reverse auction (OMSMARA), which effectively improves procurement efficiency reduces costs risks, under mixed uncertainty. Specifically, main innovation work includes three aspects: Firstly, trapezoidal fuzzy numbers applied describe uncertain bidding attribute values suppliers. Secondly, hesitant sets theory introduced characterize buyer’s satisfaction degrees evaluation information, weights determined using maximizing deviation method. Thirdly, multi-objective integer programming model solve selection quantity allocation question OMSMARA. A numerical example given demonstrate feasibility effectiveness framework, sensitivity analysis comparison further show robustness reliability solution