## 1 Introduction  
With the continuous improvement of people's living standards and quality, more attention has been paid to green and healthy lifestyles, as well as increasing demands for agricultural products. In today's complicated and volatile environmental conditions, sustainable and stable supply of green agricultural products largely depends on a highly efficient supply chain [1]. Among the whole production process, the supplying of primal material is regarded as a crucial and indispensable link in the chain [2]. That is, supplier selection has a significant impact on today's agricultural industry, especially for agribusinesses and even the government. With the pace of agricultural modernization advances continuing to increase, agricultural supply chain (ASC) holds a dominant position in agricultural socialization services [3]. After the production of primary agricultural products, ASC includes several other core operations: storage, processing, distribution, and consumption, which is presented in Figure 1[4]. Differing from other existing industries, several unique characteristics of agriculture industry are [2]: (1) In most situations, each participant in the complete ASC system is probably from separated geographical locations all around the world, encompassing farmers, processors, distributors, and retailers, so the agricultural products purchased by final consumers belong to diverse farms, various areas, and markets. (2) As a kind of product with enormous variety and quantity, it requires high functions of marketing channels; however, because of the contradiction between the regionality of production and the universality of consumption, the distribution channel is more complicated. (3) Restricted and influenced by natural conditions, the output is unstable. Furthermore, a contradiction between supply and demand also exists pervasively. The safety of the agricultural products needs more attention and concern [5]. From the perspective of sustainability, it is a worldwide trend that agricultural enterprises are increasingly actively implementing green public procurement (GPP) [6; 7] in order to better achieve economic and environmental benefits. Moreover, the development of green products has practical significance for protecting the ecological environment, improving the quality of agricultural products, promoting the development of food industry, as well as improving people's health [1]. Thus, as for an enterprise, how to pick up the optimal green agricultural product supplier under a highly uncertain decision-making environment is particularly important. Regarding the supplier selection, an expert must select the optimal one from several feasible alternatives according to a group of defined criteria, so the issue of green agricultural product supplier selection is identified as a classical multicriteria decision-making (MCDM) problem [8; 9; 10]. The most basic and crucial process of handling this issue is collecting the evaluation information provided by experts. However, in most of the practical cases, many factors may impact the decision behaviors of decision makers (DMs), such as the increasingly complicated decision-making environment, uneven levels of expertise, various personalities, as well as subjective judgments, all of which limit the ability of experts to express their actual preference information accurately. That is, this situation may result in the appearance of vagueness and uncertainty for decision-making. Thus, some uncertain techniques, such as fuzzy sets (FSs) [11], intuitionistic FSs (IFSs) [12] and Pythagorean FSs (PFSs) [13], etc., have been introduced to tackle such cases. As is well known, the notion of FSs was originally proposed by [PERSON] [11], which can assist DMs in expressing the imprecision in the assessment procedure by means of several crisp numbers.