提出血液供应链的数学模型,考虑采集中心的效率和M/M/C/K队列系统中元启发算法的开发
Meysam Karamipour1, Mehrdad Agha Mohammad Ali Kermani1
1Iran University of Science and Technology, School of Management, Economics and Progress Engineering, Iran.
Cerebral cortex (New York, N.Y. : 1991)
|January 24, 2024
概括
这项研究优化了血液供应链,降低了成本和献血者等待时间. 在提高血液采集效率方面,NSGAII算法被证明比MOPSO更有效.
科学领域:
- 运营研究 运营研究
- 医疗保健管理的管理
- 输血服务 输血服务
背景情况:
- 优化血液供应链对于有效的医疗保健服务至关重要.
- 平衡成本,捐助者经验和服务效率是一个复杂的挑战.
研究的目的:
- 开发和验证血液供应链管理的多目标模型.
- 为了最大限度地降低成本,减少捐赠者等待时间,提高收藏中心的效率.
- 在这种情况下,比较NSGAII和MOPSO算法的性能.
主要方法:
- 制定了一个包含容量和转移约束的多目标数学模型.
- 使用元启发式算法,特别是NSGAII和MOPSO,用于模型分析.
- 验证了模型的可扩展性发现.
主要成果:
- 与MOPSO算法相比,NSGAII算法显示出更高的性能.
- 该模型成功地解决了与降低成本和提高效率相关的目标.
- 确定模糊不确定性和公平分配可能不是核心问题的首要问题.
结论:
- 开发的多目标模型为血液供应链优化提供了一个强大的框架.
- 对于这个特定的血液供应链问题,NSGAII是一个更有效的算法.
- 建议对诸如血液供应链中的模糊不确定性等领域进行进一步的研究.
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