AHP–TOPSIS–PROMETHEE Hybrid Decision Support Framework for Sustainable Pharmaceutical Cold Chain Vendor Selection

Selecting pharmaceutical suppliers is a crucial process to ensure effective procurement, availability of medicines, compliance with regulations, and sustainable operation of the distribution system. This study proposes a combined Multicriteria Decision Support System (DSS) to prioritize vendors in pharmaceutical cold chain logistics. This study uses Likert AHP, TOPSIS, and PROMETHEE with 5 vendors, 4 characteristics of which are Price, Capacity, Service, and Time, supported by 20 supporting sub-characteristics. There are 10 experts related to procurement and logistics, accompanied by original operational performance data from the institution. AHP analysis shows that delivery time has an importance level of 0.534, while price is 0.200, Capacity is 0.161, and service is 0.105. In the consistency test with Hamming, Euclidean, and Spearman similarities, accompanied by sensitivity tests for each variable. The results obtained by vendor V obtained a high position with AHP and PROMETHEE, while continued with TOPSIS which is on two paths in each path. However, other vendors showed slightly different results, with Euclidean having an average of 59%. The results shown are those that have static changes due to various expert opinions. Thus, a more transparent framework is provided.