A decision algorithm for selecting the design scheme for blockchain-based agricultural product traceability system in q-rung orthopair fuzzy environment

The safety of agricultural products has always been a matter of great concern to people. To address this concern, many blockchain-based agricultural product traceability systems (BAPTSs) have been constructed. The implementation of such systems necessitates the selection of an appropriate design scheme. However, due to the diversity of agricultural products and the uncertainty of the environment, selecting an adequate design scheme for BAPTS is a difficult task for decision-makers. Because the q-rung orthopair fuzzy (q-ROF) set can dynamically delineate the space of uncertain information, this paper proposes a decision algorithm for selecting a design scheme for BAPTS using the q-ROF set. Herein, we first combine the Muirhead mean operator and power operator to develop the q-ROF power Muirhead Mean (q-ROFPMM) operator and the q-ROF weighted power Muirhead Mean (q-ROFWPMM) operator. Then, we investigate several properties of the proposed operators. Further, we construct a novel multi criteria decision-making framework for evaluating and selecting the design scheme for BAPTS based on the q-ROFWPMM operator. Next, a case study on BAPTS selection is presented to validate our method. Finally, the results of sensitivity and comparative analyses are provided to verify the efficiency and accuracy of our method. The results show that our method can effectively address the issues of BAPTS evaluation and selection, capture the relationships between any number of criteria, and eliminate the negative effects of abnormal expert evaluation values on decision-making results. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This study proposes a decision algorithm for selecting a design scheme for blockchain-based agricultural product traceability systems using the q-rung orthopair fuzzy set. By introducing novel operators to construct a multi criteria decision-making framework, the method addresses the difficulty of implementation and is validated through a case study and analysis for efficiency and accuracy.