Supplier Selection in Health Care Using Multi-Criteria Decision-Making Technique

The proper selection of medical devices from suppliers is necessary in hospital management to provide best medical essentials and treatment. Obtaining sustainable medical devices by assessing the suppliers based on different criteria such as economic, environment, social is considered as a Multi-Criteria Decision-Making (MCDM) problem. This paper proposes a novel K-mean Cluster based Heuristic Sampling method with Utopia-Pareto Directing Adaptive strategy (KCHS-UPDA). The Utopia-Pareto Directing Adaptive (UPDA) method focuses on obtaining Pareto optimal front which results in optimal solutions representing the hidden insights between objectives that help in decision making. The K-mean Cluster based Heuristic Sampling (KCHS) partitions the data into clusters which provides an explicit sampling technique with global optimization and enhances the convergence speed. A MCDM based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is employed in this research to provide ranking for effective decisions. The TOPSIS method maximizes the benefit criteria with positive-ideal solution by comparing with an ideal solution. The proposed KCHS-UPDA method is evaluated by the collected data and the performance is analyzed with total cost, service level, inventory level which achieved 130, 0.98, 195 score for 2 grouped suppliers.