Multi-Objective Optimization of Blood Products Supply Network to Minimize Delivery Time and Non-Estimated Hospital Demand

Subject Areas : Health Management Services

Zeinab Kazemi ¹ , Mahdi Homayounfar ² , mehdi fadaei ³ , Mansour Soufi ⁴ , Ali salehzadeh ⁵

1 - PhD Candidate, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran
2 - Assistant Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran
3 - Assistant Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran
4 - Assistant Professor, Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran
5 - Assistant Professor, Department of Biology, Rasht Branch, Islamic Azad University, Rasht, Iran

Received: 2022-05-30 Accepted : 2022-07-11 Published : 2022-02-20

Keywords: Blood product supply network, Meta-Heuristic Algorithm, hybrid approach, Multi-objective optimization,

Abstract :

Introduction: Due to the importance of blood as a vital element in the health system, in this study, the blood supply chain is modeled at three levels of donors, banks (blood centers) and hospitals in the form of a multi-objective model to minimize total costs, total delivery time of blood units and non-estimated demand of hospitals in each period.Methods: The present study is applied in terms of purpose and descriptive and quantitative in terms of method. The data needed to implement the real problem in 2021 have been collected by through the regional office of the Tehran blood transfusion organization along with the Negareh system. Due to the Np-hard nature of the problem, the proposed model is solved using three algorithms of GA, NSGA-II and MOPSO in GAMS software.Results: In the proposed model, matching the blood type in meeting demand; blood type delivery and allocation system in laboratories and blood banks, blood wasting in laboratory, transfer of products between demand centers, sensitive and determinative parameters of the model such as; demand, blood donation and delivery time of blood products between network components are considered indefinitely. The findings show that the MOPSO algorithm has a better performance in problems 3, 7, 10 and 12 for the QM index, but generally, based on running times and their average, the NSGA-II algorithm is better.Conclusion: Based on the results, the proposed model leads to a reduction in total costs, total delivery time of blood units and unapproved demand of hospitals.

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