Clarivate Optimal Livestock via Enigmatic Nature of Blended Decision-Making Paradigm: Practicing Comparative Methodologies

Abstract

Deployment of the intelligent technologies of information and communication technologies (ICTs) in livestock farming has positive impact and transforms it into precision livestock farm (PrLF). As well the concept of smart livestock farming is paired with technologies of Internet of Things (IoTs), virtual reality (VR), artificial intelligence (AI)…etc. The objectives of smart livestock are enriching the livestock industry's operational efficiency, ecological sustainability, and economic viability. Thus, a variety of aspects, such as human resources, product prices (both agricultural and livestock), animal welfare, and environmental sustainability, will benefit from real livestock farming using technologies of blockchain (BC), digital twin (DT) and management. Accordingly, determining the best livestock that embracing the technologies of ICTs to be precision and smart is inevitable. Therefore, this study constructed a robust paradigm to take responsibility of selecting the smartest livestock farming. Criteria Importance Through Intercriteria Correlation (CRITIC) and Multi-Attribute Rating Comparison and Improvement Analysis (MARCIA) of multi-criteria decision making (MCDM) methods are integrated to analyze the alternatives of livestock framings based on set of criteria and obtaining weights for the determined criteria through CRITIC. These weights of criteria are leveraging into MAIRCA to rank the alternatives of livestock farming. The primary characteristic of this paradigm is its ability to treat incomplete and uncertain information due to collaborating uncertainty theory as single valued neutrosophic (SVN). For validating the robustness of constructed paradigm, we applied it into real case study and comparing it with other methods. The findings of the applied methods agree with constructed paradigm’s findings.