From Models to Meaning in Decision Intelligence: IMEREC–PNS with a Streamlit-Based Decision Support System for Uncertain MCDM

Abstract

Multi-criteria decision making approaches are extensively applied to solve complex decision problems with multiple, conflicting criteria, and uncertainty. However, current objective weighting methods, such as MEREC, are primarily developed for crisp decision-making environments and are not suitable for considering indeterminacy and hesitation, and target-based criteria. In this regard, this paper introduces an Improved MEREC method with Pythagorean Neutrosophic Sets (IMEREC–PNS) to determine the objective weights of criteria under uncertain conditions. The new method extends the removal effect mechanism of MEREC to the PNS environment and improves the handling of benefit, cost, and target-based criteria. Furthermore, a decision support system based on the Streamlit framework has been developed to automate the computational process and improve the transparency, accessibility, and reproducibility of the proposed model. A case study of logistic provider selection is provided to illustrate the proposed approach, and the findings demonstrate that the proposed IMEREC-PNS model is capable of determining reasonable criterion weights and the Streamlit platform provides interactive input, automatic calculation, and visualization of results. The framework offers an effective and flexible approach for objective weighting in uncertain multi-criteria decision making.