Prioritization of drip-irrigation pump alternatives in agricultural applications: An integrated picture fuzzy BWM&CODAS methodology

Abstract

One of the irrigation methods is drip irrigation, for which selecting the right pump has a significant impact. In this study, the process of choosing the appropriate pump for drip irrigation is regarded as a multi-criteria decision-making (MCDM) problem. The objective is to enhance productivity and minimize water consumption in agricultural areas by addressing the drip-irrigation pump-selection problem. Making decisions under uncertainty is a complex task, especially when dealing with intricate problems where complexity raises concerns about finding more dependable solutions. Fuzzy extensions of MCDM methods are designed to tackle such intricate and detailed problems compared to traditional MCDM methods. Therefore, we propose and implement a Picture Fuzzy CODAS (PF-CODAS) method to address the issue of drip-irrigation pump selection under vagueness, utilizing expert opinions. In comparison to other MCDM methods, our suggested approach combines multi-criteria decision analysis with picture fuzzy hesitancy and a negative ideal solution, supported by Euclidean and Taxicab distances. Furthermore, we present an integrated approach that uses the Best Worst Method (BWM) to determine criterion weights and the PF-CODAS method for ranking alternatives. Overall, this study offers valuable support for advancing sustainable agriculture through our proposed MCDM approach.