An analytical framework for baby milk products selection using decision making techniques

• IMNC criteria to assess BMCs for infants from birth is used • Dynamic decision matrix for BMCs via the two methodologies is established • 2TLq-RPF-SWARA to assign weights for IMNC criteria is implemented • CRADIS model to benchmark BMCs is used. • Sensitivity analysis to measure the proposed weight effects is used Ensuring that infant formulas meet the nutritional and safety standards of the World Health Organization is of critical importance. This study introduces a novel multicriteria decision-making (MCDM) framework, enhanced with fuzzy logic, to evaluate Baby Milk Companies (BMCs). The framework integrates two advanced methods: the 2-Tuple Linguistic q-Rung Picture Fuzzy Stepwise Weighted Assessment Ratio Analysis (2TLq-RPF-SWARA) for determining the weights of nutritional criteria, and the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) for ranking BMC products. Data from ten major BMCs were analyzed, with company names anonymized to ensure objectivity. Infant Milk Nutritional Contents (IMNCs) were assessed, focusing on key components such as proteins, carbohydrates, vitamins, and minerals. Results showed that BMC 2 achieved the highest score due to its balanced profile of macronutrients, essential fatty acids, and a rich spectrum of vitamins, minerals, and functional additives, whereas BMC 5 ranked lowest, reflecting significant deficiencies in essential nutritional factors. A sensitivity analysis further demonstrated that variations in criteria weights had only a moderate effect on the rankings, underscoring the robustness of the framework. Overall, the proposed approach enhances accuracy, transparency, and flexibility in evaluating infant nutrition products, providing a valuable tool to support evidence-based decision-making in the infant nutrition industry.