Assessment of Agriculture Crop Selection Using Pythagorean Fuzzy CRITIC–VIKOR Decision-Making Framework

The assessment of best agriculture crop pattern has an important influence on the feasibility of a sustainable farming process. The process of agriculture crop assessment can be regarded as an uncertain multi-criteria decision-making (MCDM) concern due to the association of many tangible and intangible criteria. Pythagorean fuzzy set (PFS) has proven as one of the interesting tools to describe the uncertain information. This chapter presents a new hybrid model with CRITIC and VIKOR methods and employs to solve the Kharif crop selection problem of Satna district in Madhya Pradesh, India. In this model, the criteria weights are computed by the CRITIC approach and the preference order of Kharif crops is evaluated by VIKOR model, which provides easy mathematical steps with accurate and consistent results for assessing the crops. In addition, new divergence and entropy measures are developed to assess the compromise measure and compute the experts’ importance degrees, respectively. To exhibit the practicality of the introduced model, a case study of Kharif crop assessment of Satna district is offered within PFSs environment. Moreover, we exhibit a sensitivity analysis over parameter values in view of examining the stability of our proposed approach. At the end of this study, we draw attention towards a comparison between our proposed PF-CRITIC–VIKOR decision-making approach with an existing TOPSIS method to show its superiority and potency as well. The proposed model can be applied across the world to choose an optimal crop for promoting sustainable agricultural practices and maximizing profits.