Optimizing Blockchain Platform Selection: A Decision-Making Approach Using LLMs, Type-2 Neutrosophic Numbers, CRITIC, and MAIRCA

Blockchain (BC) platforms integrated with Generative AI (GenAI) like Large Language Models (LLMs) are the basic infrastructure for significant consumer data like Bitcoin and Smart Contracts systems, addressing challenges such as protection from anomalous transactions, automation, and easier to interact with BC platforms using LLMs. There are a lot of BC platforms with different characteristics. The problem of variety and uncertainty of characteristics in evaluating and ranking the most appropriate BC platforms integrated with LLMs can be approached as a multicriteria decision-making (MCDM) problem. In this research paper, we used a hybrid T2NN-CRITICMAIRCA MCDM approach that combines Type-2 Neutrosophic Number (T2NN) to handle uncertain information with The Criteria Importance Through Intercriteria Correlation (CRITIC) to assign objective weights to criteria and The Multi Attributive Ideal-Real Comparative Analysis (MAIRCA) to evaluate and rank ten BC platforms integrated with LLMs from different BC platform types (like public, private, and hybrid BC platforms) against three key dimensions: technological, organizational, and environmental. The results indicate that Stellar (BC5), Continuous Klaytn (BC8), Openchain (BC4), and Hyperledger Fabric (BC2) are the top-ranked alternatives BC platforms integrated with LLMs. These findings are significant. Helping business sectors that use Bicton, smart contracts, or other BC applications as a comprehensive tool to evaluate and rank optimal BC platforms integrated with LLMs. It contributes in increasing security, automation, and easier interaction with BC platforms.