Robust-Fuzzy-Probabilistic Programming for a Multi-Echelon Drug Supply Chain Network under Uncertainty
Subject Areas :امین طغیانی 1 * , سید اسماعیل نجفی 2 , Neda Rafieeparsa 3
1 -
2 -
3 - Department of Industrial Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran
Keywords: Drug supply chain network, Robust-fuzzy-probabilistic, programming, Uncertainty, Quantitydiscount, Perishability, NSGA-II, MOWOA,
Abstract :
Objective: This study aims to design a multi-echelon pharmaceutical supply chain network under uncertainty. The main objectives are to minimize total network costs and maximum unmet demand while maximizing the reliability of drug delivery to end customers. Methodology: A robust-fuzzy-probabilistic (RFP) programming approach is employed to control uncertain parameters in the pharmaceutical supply chain network. The proposed network consists of five echelons: suppliers, manufacturers, distributors, retailers, and customers. The model also considers general discounts on manufacturers’ raw material purchases and the reliability of drug delivery. A multi-objective decision-making approach is applied to solve small-scale instances, while NSGA-II and MOWOA algorithms are used for larger-scale problems. Conclusion: The computational results indicate that increasing uncertainty levels leads to higher total network design costs and greater shortages. The sensitivity analysis of perishability time shows that increasing this parameter reduces total network costs and shortages while improving the reliability of perishable product delivery. Furthermore, 15 test problems of different sizes are developed for large-scale evaluation. The results indicate no significant difference between the mean performance of the algorithms across the evaluated indices. Originality: The originality of this research lies in developing a multi-objective pharmaceutical supply chain network model that integrates robust-fuzzy-probabilistic programming, general raw material purchase discounts, product perishability, delivery reliability, and unmet demand under uncertainty. Originality: The originality of this research lies in developing a multi-objective pharmaceutical supply chain network model that integrates robust-fuzzy-probabilistic programming, general raw material purchase discounts, product perishability, delivery reliability, and unmet demand under uncertainty
Akbarpour, M., Torabi, S. A., & Ghavamifar, A. (2020). Designing an integrated pharmaceutical relief chain network under demand uncertainty. Transportation Research Part E: Logistics and Transportation Review, 136,101867
Aliahmadi, A., Ghahremani-Nahr, J., & Nozari, H. (2023). Pricing decisions in the closed-loop supply chain network, taking into account the queuing system in production centers. Expert Systems with Applications, 212, 118741.
Alkaabneh, F., Diabat, A., & Gao, H. O. (2020). Benders decomposition for the inventory vehicle routing problem with perishable products and environmental costs. Computers & Operations Research, 113, 104751.
Baboli, A., Fondrevelle, J., Tavakkoli-Moghaddam, R., & Mehrabi, A. (2011). A replenishment policy based on joint optimization in a downstream pharmaceutical supply chain: centralized vs. decentralized replenishment. The International Journal of Advanced Manufacturing Technology, 57(1–4), 367–378.
Biuki, M., Kazemi, A., & Alinezhad, A. (2020). An integrated location–routing–inventory model for sustainable design of a perishable products supply chain network. Journal of Cleaner Production, 260,120842.
Diabat, A., Abdallah, T., & Le, T. (2016). A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods. Annals of Operations Research, 242(2), 373–398.
Mardan, E., Govindan, K., Mina, H., & Gholami-Zanjani, S. M. (2019). An accelerated benders decomposition algorithm for a bi-objective green closed loop supply chain network design problem. Journal of Cleaner Production, 235, 1499–1514.
Masoumi, A. H., Yu, M., & Nagurney, A. (2012). A supply chain generalized network oligopoly model for pharmaceuticals under brand diferentiation and perishability. Transportation Research Part E: Logistics and Transportation Review, 48(4), 762–780.
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.
Nagurney, A., & Li, D. (2015). A supply chain network game theory model with product diferentiation, outsourcing of production and distribution, and quality and price competition. Annals of Operations Research, 226(1), 479–503.
Nasrollahi, M., & Razmi, J. (2019). A mathematical model for designing an integrated pharmaceutical supply chain with maximum expected coverage under uncertainty. Operational Research, 1–28.
Nozari, H., & Aliahmadi, A. (2022). Lean supply chain based on IoT and blockchain: Quantitative analysis of critical success factors (CSF). Journal of Industrial and Systems Engineering, 14(3), 149-167.
Nozari, H., Tavakkoli-Moghaddam, R., & Gharemani-Nahr, J. (2022). A neutrosophic fuzzy programming method to solve a multi-depot vehicle routing model under uncertainty during the covid-19 pandemic. International Journal of Engineering, 35(2), 360-371.
Ozsen, L., Coullard, C. R., & Daskin, M. S. (2008). Capacitated warehouse location model with risk pooling. Naval Research Logistics (NRL), 55(4), 295–312.
Sabouhi, F., Pishvaee, M. S., & Jabalameli, M. S. (2018). Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain. Computers & Industrial Engineering, 126,657–672.
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.
Singh, S. K., & Goh, M. (2018). Multi-objective mixed integer programming and an application in a pharmaceutical supply chain. International Journal of Production Research, 57,124.
Aliahmadi, A., & Nozari, H. (2023, January). Evaluation of security metrics in AIoT and blockchain-based supply chain by Neutrosophic decision-making method. In Supply Chain Forum: An International Journal (Vol. 24, No. 1, pp. 31-42). Taylor & Francis.
Weraikat, D., Zanjani, M. K., & Lehoux, N. (2016). Two-echelon pharmaceutical reverse supply chain coordination with customers incentives. International Journal of Production Economics, 176,41–52.
Weraikat, D., Zanjani, M. K., & Lehoux, N. (2019). Improving sustainability in a two-level pharmaceutical supply chain through vendor-managed inventory system. Operations Research for Health Care,21,44–55.
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.
Zahiri, B., Zhuang, J., & Mohammadi, M. (2017). Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transportation Research Part E: Logistics and Transportation Review, 103,109–142