Document Type : Original Article


1 Ph.D Student, Yazd University.

2 Associate Professor, Yazd University.

3 Professor, Yazd University.


Developing efficient and effective health care systems has become a major concern for governments and health care decision makers. In-time supply of medicine and efficiency of the inventory and distribution system play a vital role in the hospital supply chain and require a proper decision-making process in inventory management. This study suggests a two-objective model of mixed-integer, linear programming to manage medicine and information flow. The main goals of this model are to minimize the costs of purchasing, maintaining, manpower, and medicine expiration, and to minimize medicine shortages. Uncertainty parameters are related to demand, storage, and supply capacity, as well as the aspiration level of each goal. The initial model is first transformed into a fuzzy mixed-integer, goal programming model. Then, the resulting model is transformed into a one-objective model using methods suggested by Torabi and Hassini and solved in GAMS. The supply chain of Shahid Beheshti Hospital in Kashan is used to explain the proposed approach. The results indicate that decisions related to the purchase and logistics of medicine have a great impact on medicine shortages and control various costs relating to medicine inventory in this hospital.


Main Subjects

  1. Abu Zwaida, T., Pham, C., & Beauregard, Y. (2021). Optimization of Inventory Management to Prevent Drug Shortages in the Hospital Supply Chain. Applied Sciences, 11(6), 2726.
  2. Ahmadi, A., Mousazadeh, M., Torabi, S. A., & Pishvaee, M. S. (2018). OR Applications in Pharmaceutical Supply Chain Management. In C. Kahraman & Y. I. Topcu (Eds.), Operations Research Applications in Health Care Management (pp. 461-491). Springer International Publishing.
  3. Ding, B. (2018). Pharma industry 4.0: Literature review and research opportunities in sustainable pharmaceutical supply chains. Process Safety and Environmental Protection, 119, 115-130.
  4. Duque-Uribe, V., Sarache, W., & Gutiérrez, E. V. (2019). Sustainable supply chain management practices and sustainable performance in hospitals: a systematic review and integrative framework. Sustainability, 11(21), 5949.
  5. Franco, C., & Alfonso-Lizarazo, E. (2020). Optimization under uncertainty of the pharmaceutical supply chain in hospitals. Computers & Chemical Engineering, 135, 106689.
  6. Foukerdi, R., & Talavari, Z. (2021). Cash flow Optimization in Medicine Supply Chain: A Supply Risk Approach. The journal of Industrial Management Perspective, 11(1), 117-145. (In Persian)
  7. Goodarzian, F., Taleizadeh, A. A., Ghasemi, P., & Abraham, A. (2021). An integrated sustainable medical supply chain network during COVID-19. Engineering Applications of Artificial Intelligence, 100, 104188.
  8. Hans, E. W., van Houdenhoven, M., & Hulshof, P. J. H. (2012). A Framework for Healthcare Planning and Control. In R. Hall (Ed.), Handbook of Healthcare System Scheduling (pp. 303-320). Springer US.
  9. Jiménez, M., Arenas, M., Bilbao, A., & Rodrı´guez, M. V. (2007). Linear programming with fuzzy parameters: An interactive method resolution. European Journal of Operational Research, 177(3), 1599-1609.
  10. Kalantari, M., Pishvaee, M. S., & Yaghoubi, S. (2015). A Multi Objective Model Integrating Financial and Material Flow in Supply Chain Master Planning. The Journal of Industrial Management Perspective, 5(3), 139-167.
  11. Kees, M. C., Bandoni, J. A., & Moreno, M. S. (2019). An Optimization Model for Managing the Drug Logistics Process in a Public Hospital Supply Chain Integrating Physical and Economic Flows. Industrial & Engineering Chemistry Research, 58(9), 3767-3781.
  12. Kouchaki-Tajani, T., Mohtashami, A., Amiri, M., & Ehtesham-Rasi, R. (2021). Presenting a Robust Optimization Model to Design a Comprehensive Blood Supply Chain under Supply and Demand Uncertainties. The journal of Industrial Management Perspective, 11(1), 81-116. (In Persian)
  13. Mousazadeh, M., Torabi, S. A., & Zahiri, B. (2015). A robust possibilistic programming approach for pharmaceutical supply chain network design. Computers & Chemical Engineering, 82, 115-128.
  14. Narayana, S. A., Pati, R. K., & Vrat, P. (2014). Managerial research on the pharmaceutical supply chain–A critical review and some insights for future directions. Journal of Purchasing and Supply Management, 20(1), 18-40.
  15. Peidro, D., Mula, J., Jiménez, M., & del Mar Botella, M. (2010). A fuzzy linear programming-based approach for tactical supply chain planning in an uncertainty environment. European Journal of Operational Research, 205(1), 65-80.
  16. Rakovska, M. A., & Stratieva, S. V. (2018). A taxonomy of healthcare supply chain management practices. Supply Chain Forum: An International Journal, 19(1), 4-24.
  17. Rappold, J., Van Roo, B., Di Martinelly, C., & Riane, F. (2011). An Inventory Optimization Model To Support Operating Room Schedules. Supply Chain Forum: An International Journal, 12(1), 56-69.
  18. Roshan, M., Tavakkoli-Moghaddam, R., & Rahimi, Y. (2019). A two-stage approach to agile pharmaceutical supply chain management with product substitutability in crises. Computers & Chemical Engineering, 127, 200-217.
  19. Roy, S., Prasanna Venkatesan, S., & Goh, M. (2020). Healthcare services: A systematic review of patient-centric logistics issues using simulation. Journal of the Operational Research Society, 72(10), 2342-2364.
  20. Saha, E., & Ray, P. K. (2019). Modelling and analysis of inventory management systems in healthcare: A review and reflections. Computers & Industrial Engineering, 137,
  21. Savadkoohi, E., Mousazadeh, M., & Torabi, S. A. (2018). A possibilistic location-inventory model for multi-period perishable pharmaceutical supply chain network design. Chemical Engineering Research and Design, 138, 490-505.
  22. Sazvar, Z., Zokaee, M., Tavakkoli-Moghaddam, R., Salari, S. A.-s., & Nayeri, S. (2021). Designing a sustainable closed-loop pharmaceutical supply chain in a competitive market considering demand uncertainty, manufacturer’s brand and waste management. Annals of Operations Research, 1-32.
  23. Shakouhi, F. S., Tavakkoli-Moghaddam, R., Baboli, A., & Bozorgi-Amiri, A. (2020). Fuzzy Goal Programming Based on a Taylor Series for a Pharmaceutical Supply Chain with a Marketing Mix Strategy and Product Life Cycle. In Smart and Sustainable Supply Chain and Logistics–Trends, Challenges, Methods and Best Practices (pp. 395-406). Springer.
  24. Singh, S. K., & Goh, M. (2019). Multi-objective mixed integer programming and an application in a pharmaceutical supply chain. International Journal of Production Research, 57(4), 1214-1237.
  25. Torabi, S. A., & Hassini, E. (2009). Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach. International Journal of Production Research, 47(19), 5475-5499.
  26. Uthayakumar, R., & Priyan, S. (2013). Pharmaceutical supply chain and inventory management strategies: Optimization for a pharmaceutical company and a hospital. Operations Research for Health Care, 2(3), 52-64.
  27. Volland, J., Fügener, A., Schoenfelder, J., & Brunner, J. O. (2017). Material logistics in hospitals: A literature review. Omega, 69, 82-101.
  28. Zahiri, B., Jula, P., & Tavakkoli-Moghaddam, R. (2018). Design of a pharmaceutical supply chain network under uncertainty considering perishability and substitutability of products. Information Sciences, 423, 257-283.
  29. Zandkarimkhani, S., Mina, H., Biuki, M., & Govindan, K. (2020). A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design. Annals of Operations Research, 295(1), 425-452.
  30. Zimmermann, H. J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1(1), 45-55.
  31. Zwaida, T. A., Beauregard, Y., & Elarroudi, K. (2019). Comprehensive literature review about drug shortages in the canadian hospital's pharmacy supply chain. 2019 International Conference on Engineering, Science, and Industrial Applications (ICESI).