Enhancing Project Selection with Neutrosophic TOPSIS: Navigating Uncertainty in Post-Pandemic Decision-Making

Abstract

This article explores the implementation of Neutrosophic TOPSIS, an advanced decision-making framework that extends classical and fuzzy set theories to handle the complexities of project selection amid uncertainty and indeterminacy. Neutrosophic sets are characterized by three parameters: truth, indeterminacy, and falsehood, which allow for a nuanced assessment of alternatives against defined criteria. Utilizing neutrosophic scales and expert evaluations, this method prioritizes projects by efficiently balancing multiple truth levels and addressing specific challenges such as judicial process optimization and labor education enhancement. The case study within the article demonstrates the application of Neutrosophic TOPSIS to select the most suitable project for improving labor relations and judicial efficiency in a post-pandemic world. The methodology proved effective in identifying the Digital Platform for Labor Education project as the optimal solution, given its alignment with strategic objectives and potential to handle identified challenges robustly. Future work could integrate Neutrosophic TOPSIS with other decision-making models and expand its application to more complex scenarios, potentially incorporating automated tools for a broader and more dynamic evaluation process.