Planning for pharma supply chain under uncertainty considering inventory optimization

Article type: Research Article

Authors: Birong, Zhang^{; *}

Affiliations: College of Economics and Management, Quanzhou University of Information Engineering, Quanzhou, Fujian, China

Correspondence: [*] Corresponding author. Zhang Birong, College of Economics and Management, Quanzhou University of Information Engineering, Quanzhou, Fujian, China. E-mail: [email protected].

Abstract: In this paper, a bi-objective mixed-integer linear programming model is constructed to manage the pharmaceutical supply chain of a hospital. The proposed model aims to concurrently reduce the overall cost of obtaining drugs from several vendors and choose the best suitable source. The suggested model takes into account supplier distance, inventory management, and multi-product and multi-period. The major assumptions of the proposed model are product storage for future periods of decreased demand and supplier capacity. The results indicate that the ideal approach can minimize hospital supply and pharmaceutical planning expenses. The Best-Worst and TOPSIS methods determine which pharmaceutical supplier should be selected for future orders. The suggested model identifies human resource capability as an essential factor that might significantly affect the system’s total cost. The results of applying the model and the sensitivity analysis validate the efficacy and validity of the suggested mathematical model and solution strategy.

Keywords: Optimization, pharma supply chain, uncertainty, robust programming

DOI: 10.3233/JIFS-230017

Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 6561-6574, 2023