考虑危机情况的易腐医疗用品供应链网络模糊双目标数学模型:实证研究。

IF 2.4 Q2 HEALTH CARE SCIENCES & SERVICES Health Services Insights Pub Date : 2024-11-02 eCollection Date: 2024-01-01 DOI:10.1177/11786329241288772
Fereshteh Shahrabadi, Hamidreza Kia, Ali Heidari, Mohammad Khalilzadeh
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引用次数: 0

摘要

在危机情况下,伤员的救治取决于医疗物资、救援物资和设备的及时供应。本研究的目的是在考虑不确定环境的情况下,提出危机情况下易腐医疗物品供应链网络的数学模型。本文针对易腐医疗物品建立了包括供应商、中间仓库和最终客户在内的三级供应链。使用指数分布函数考虑了客户服务需求和中间仓库停留时间的不确定性。此外,还假设易腐医疗物品的生命周期遵循 Weibull 分布函数。该模型试图最小化供应链的总成本和易腐物品在整个供应链中的总停留时间。该模型采用 LP-Metric 方法解决小型问题。由于问题的 NP-Hardness,我们采用了改进的多目标粒子群优化算法(MOPSO)和非支配排序遗传算法(NSGA-II)这两种著名且高效的元启发式算法来解决大型问题。研究结果表明,元启发式算法能在合理的时间内高效地为大型问题找到接近最优的解决方案。此外,研究结果还表明,NSGA-II 在高质量解方面优于 MOPSO。最后,本文通过一个实际案例研究证明了该模型在实际问题中的适用性。本文可以帮助易腐药品供应链网络的规划者和决策者在危机条件下及时供应和分发所需的应急物品。
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A Fuzzy Bi-objective Mathematical Model for Perishable Medical Goods Supply Chain Network Considering Crisis Situations: An Empirical Study.

In case of crisis, the salvation of injuries depends on the timely provision of medical goods, relief supplies, and equipment. The aim of this study is to present a mathematical model for the supply chain network of perishable medical goods in crisis situation considering the uncertain environment. In this paper, a three-level supply chain including suppliers, intermediate warehouses, and final customers is developed for perishable medical items. The uncertainty of customer demand for service and the spent time in the intermediate warehouses are considered using the exponential distribution functions. Also, it is assumed that the life-cycle of perishable medical goods follow the Weibull distribution function. The model attempts to minimize the total costs of the supply chain and total presence time of perishable items in the whole chain. The LP-Metric method is employed for solving small-sized problems. Due to the NP-Hardness of the problem, the modified Multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II) are utilized as 2 well-known and efficient meta-heuristic algorithms for solving large-sized problems. The findings indicate that the meta-heuristic algorithms are efficient in achieving close to the optimal solution for large-size problems in a reasonable time. Also, the results demonstrate that NSGA-II outperforms MOPSO in terms of the high quality solution. Finally, the applicability of the model to real-world problems is demonstrated using a real case study. This paper can assist the planners and decision-makers of perishable drugs supply chain networks in crisis conditions with on-time supplying and distributing the required emergency items.

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来源期刊
Health Services Insights
Health Services Insights HEALTH CARE SCIENCES & SERVICES-
CiteScore
3.60
自引率
0.00%
发文量
47
审稿时长
8 weeks
期刊最新文献
Corrigendum to "Healthcare Professionals' Resilience during the COVID-19 and Organizational Factors That Improve Individual Resilience: A Mixed-Method Study". A Fuzzy Bi-objective Mathematical Model for Perishable Medical Goods Supply Chain Network Considering Crisis Situations: An Empirical Study. Procedure Prioritization During a Nationwide Ban on Non-Urgent Healthcare: A Quasi-Experimental Retrospective Study of Hospital Data in Switzerland. Navigating Rehabilitation Transitions at Street Level: A Qualitative Analysis of Municipal Service Allocation to Individuals With Complex Needs. Patterns of Antidepressant and Anxiolytic Use and Spending in 14 European Countries (2012-2021): A Comprehensive Time Series Analysis.
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