A Dynamic Simulation-Optimization Approach for Inventory Management of Multi-Product Hospital Pharmacies in Discrete Time

Document Type : Research Paper

Authors

1 PhD in Industrial Management, Mathematics Secretary of Education, Bushehr, Iran.

2 Associate Prof., Department of Industrial Management, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran.

3 Assistant Prof., Department of Industrial Management, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran

4 Assistant Prof., Department of Nutrition, Faculty of Health, Bushehr University of Medical Sciences and Health Services, Bushehr, Iran.

10.22059/imj.2025.361793.1008110

Abstract

Objective: In the patient care chain, medicines are essential items and play a critical role in patient recovery. Inefficient inventory management leads to drug shortages, lack of continuity of drug inventory, reduced patient safety, poor performance, distribution defects, and technological errors, which lead to drug shortages in hospital pharmacies. Providing an efficient approach can minimize costs in the supply chain.
Methods: This study presented a simulation-optimization model for pharmacy inventory management. A training-learning-based optimization algorithm was used to solve the model. The model was programmed and solved in MATLAB software. 
Results: Given that the initial inventory is assumed to be zero, the drug price is lower at the beginning of the year, and the number of patients is lower than in the summer. Therefore, the volume of orders is high at the start of the year. The model adjusts the level of orders so that the costs are minimal. As the disease re-emerges and the number of patients increases, demand increases in the ninth and tenth months, and the volume of orders increases again. As demand decreases at the end of the year, the volume of orders also decreases.
Conclusion: By implementing the model during the planning period, while minimizing system costs, the inventory level for all drug categories will be at the desired level, and no inventory shortages will occur.

Keywords

References

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. DOI: 10.3390/app11062726.
Akbari, E., Ghasemi, M., Gil, M., Rahimnejad, A., & Andrew Gadsden, S. (2022). Optimal power flow via teaching-learning-studying-based optimization algorithm. Electric Power Components and Systems, 49(6-7), 584–601. DOI: 10.1080/15325008.2021.1971331.
Antonoglou, D., Kastanioti, C., & Niakas, D. (2017). ABC and VED analysis of medical materials of a general military hospital in Greece. Journal of Health Management, 19(1), 170-179. DOI: 10.1177/0972063416682643.
Buschiazzo, M., Mula, J., & Campuzano-Bolarin, F. (2020). Simulation optimization for the inventory management of healthcare supplies. International Journal of Simulation Modelling, 19(2), 255–266. DOI: 10.2507/IJSIMM19-2-514.
Chen, C. N., Lai, C. H., Lu, G. W., Huang, C. C., Wu, L. J., Lin, H. C., & Chen, P. S. (2022). Applying simulation optimization to minimize drug inventory costs: a study of a case outpatient pharmacy. In Healthcare,10(3), 556. DOI: 10.3390/healthcare10030556.
Chen, D., Zou, F., Li, Z., Wang, J., & Li, S. (2015). An improved teaching–learning-based optimization algorithm for solving global optimization problems. Information Sciences, 297, 171-190. DOI: 10.1155/2022/1535957.
Chihaoui, F. B., Maddeh, N., Layeb, S. B., Hamouda, C., & Chaouachi, J. (2019, April). A decision support system for drug inventory management within an emergency department: A case study. In 2019, the 6th International Conference on Control, Decision, and Information Technologies. IEEE. 1889-1894. DOI: 10.1109/CoDIT.2019.8820599.
Clerc, M., & Kennedy, J. (2002). The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, 6(1), 58–73. DOI: 10.1109/4235.985692.
Elarbi, M., Ayadi, O., Masmoudi, M., & Masmoudi, F. (2021). Drug-inventory-management-model for a multi-echelon pharmaceutical supply-chain: case study of the Tunisian pharmaceutical supply-chain. In Supply Chain Forum: An International Journal, 22(1), 44–56. Taylor & Francis. Chicago. DOI: 10.1080/16258312.2020.1824532.
Figueira, G., & Almada-Lobo, B. (2014). Hybrid simulation–optimization methods: A taxonomy and discussion. Simulation modelling practice and theory, 46, 118–134. DOI: 10.1016/j.ejor.2007.07.035.
Galli, L., Levato, T., Schoen, F., & Tigli, L. (2021). Prescriptive analytics for inventory management in health care, Journal of the Operational Research Society, 72(10), 2211–2224. DOI: 10.1080/01605682.2020.1776167.
García, J. A. M., & Mena, A. J. G. (2013). Optimal distributed generation location and size using a modified teaching–learning optimization algorithm. International journal of electrical power & energy systems, 50, 65–75. DOI: 10.1016/j.ijepes.2013.02.023.
Gebicki, M., Mooney, E., Chen, S. J., & Mazur, L. M. (2014). Evaluation of hospital medication inventory policies. Health care management science, 17(3), 215–229. DOI: 10.1007/s10729-013-9251-1.
Guerrero, W. J., Yeung, T. G., & Guéret, C. (2013). Joint-optimizing inventory policies on a multi-product multi-echelon pharmaceutical system with batching and ordering constraints. European Journal of Operational Research, 231(1), 98–108. DOI: 10.1016/j.ejor.2013.05.030.
Hejazi, T. H. (2021). State-dependent resource reallocation plan for health care systems: A simulation optimization approach. Computers & Industrial Engineering, 159, 107502. DOI: 10.1016/j.cie.2021.107502.
Qiu, Y., Qiao, J., & Pardalos, P. M. (2019). Optimal production, replenishment, delivery, routing, and inventory management policies for products with perishable inventory. Omega, 82, 193–204.    DOI: 10.1016/j.omega.2018.01.006.
Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2011). Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Computer-aided design, 43(3), 303–315. DOI: 10.1016/j.cad.2010.12.015.
Saedi, S., Kundakcioglu, O. E., & Henry, A. C. (2016). Mitigating the impact of drug shortages for a healthcare facility: An inventory management approach. European Journal of Operational Research, 251(1), 107-123. DOI: 10.1016/j.ejor.2015.11.017.
Scott, N. A., Lee, K. K., Sadowski, C., Kurbatova, E. V., Goldberg, S. V., Nsubuga, P., ... & Tuberculosis Trials Consortium. (2021). Optimizing drug inventory management with a web-based information system: The TBTC Study 31/ACTG A5349 experience. Contemporary clinical trials, 105, 106377. DOI: 10.1016/j.cct.2021.106377.
Shiau, J. Y. (2019). A drug association-based inventory control system for ambulatory care. Journal of Information and Optimization Sciences, 40(6), 1351-1365.  DOI: 10.1080/02522667.2019.1649032.
Wacker, J. G. (1998). A definition of theory: research guidelines for different theory-building research methods in operations management. Journal of Operations Management, 16(4), 361–385. DOI: 10.1016/S0272-6963(98)00019–9.
Wild, T. (2017). Best practice in inventory management. Routledge. DOI: 10.4324/9781315231532.
Wu, D., Wang, S., Liu, Q., Abualigah, L., & Jia, H. (2022). An Improved Teaching‐Learning‐Based Optimization Algorithm with Reinforcement Learning Strategy for Solving Optimization Problems. Computational Intelligence and Neuroscience, 2022(1), 1535957.    DOI: 10.1155/2022/1535957.
Industrial Management Journal
Volume 17, Issue 3
2025
Pages 1-17

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