Production planning and control of a pharmaceutical supply chain using evolutionary fuzzy approach

This study aims to enhance the effectiveness of planning a pharmaceutical or healthcare supply chain (PHSC). Past research mostly applied simulation or optimization methods, which were time-consuming or difficult to obtain the optimal solution. This study proposes an evolutionary fuzzy approach from a multiple-criteria decision-making (MCDM) perspective to addresses this issue. Primary factors considered in the proposed methodology include product quality, capacity, availability, experience and relationship, and product cost. In the proposed methodology, a calibrated fuzzy inverse of column sum (cFICSM) method is devised to derive the fuzzy priorities of criteria. Fuzzy principal component analysis (FPCA) is proposed to resolve the dependencies among criteria. Fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) is then applied to evaluate and compare PHSC partners. Finally, the required pieces are distributed among PHSC partners. The proposed methodology has been applied to plan a PHSC for medical masks in central Taiwan during the COVID-19 pandemic. Based on the experimental results, the proposed approach minimizes the makespan while increasing the compliance with customers' preferences by 29 %. This study concludes that planning a PHSC from an MCDM perspective can achieve synergistic effects.