一个模糊的双客观数学模型易腐坏的医疗产品供应链网络考虑危机情况:实证研究
Fereshteh Shahrabadi1, Hamidreza Kia1, Ali Heidari2
1School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
Health services insights
|November 4, 2024
概括
这项研究模拟了危机期间易损坏的医疗供应链,优化了交付时间和成本. 非主导排序基因算法 (NSGA-II) 在复杂场景中证明了高效,高质量的解决方案的优势.
科学领域:
- 运营研究 运营研究
- 供应链管理 供应链管理
- 医疗保健物流 医疗保健物流
背景情况:
- 在危机期间,及时提供医疗用品至关重要.
- 现有的模型经常与危机物流固有的不确定性作斗争.
- 易损坏的医疗用品需要专门的供应链考虑.
研究的目的:
- 开发一个数学模型,用于一个三级易腐烂的医疗供应链网络.
- 为了最大限度地优化供应链总成本和物品存在时间.
- 解决客户需求和仓库处理时间的不确定性.
主要方法:
- 利用了对需求和仓库时间不确定性的指数分布.
- 使用韦布尔分布建模易腐物品生命周期.
- 在小型问题上使用LP-Metric,在大型NP-Hard问题上使用Meta-heuristics (MOPSO,NSGA-II).
主要成果:
- 超启发式算法有效地为大规模问题找到接近最佳的解决方案.
- 在解决方案质量方面,NSGA-II在MOPSO上表现优越.
- 该模型的适用性通过现实世界的案例研究来验证.
结论:
- 开发的模型提供了一个强大的框架,用于在危机情况下管理易腐烂的医疗用品.
- 决策者可以利用这种模式,有效及时分发紧急医疗用品.
- NSGA-II是一个推的算法,用于在不确定性下优化复杂的医疗供应链.
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