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研究优化传染性医疗废物运输路线的研究
Chen Hao1, L I Libo2, Qin Xuerui1
1School of Economics and Business Administration, Yibin University, Yibin, Sichuan, China.
PloS one
|September 26, 2025
概括
这项研究优化了传染性医疗废物收集路线,降低了成本和里程. 改进的NSGA-II算法提高了医疗废物运输的效率,特别是在废物产量增加期间.
科学领域:
- 运营研究 运营研究
- 环境科学 环境科学
- 公共卫生 公共卫生
背景情况:
- 随着COVID-19的流行,传染性医疗废物产生显著增加.
- 现有的医疗废物回收面临着诸如高成本,长途运输和不足的应急响应等挑战.
- 有效的收集和路线优化对于管理这种废物流至关重要.
研究的目的:
- 开发一种优化方法,用于医疗废物收集地点的选择和车辆路线.
- 尽量减少与传染性医疗废物相关的运输成本和污染风险.
- 为了应对复杂的多车辆,多阶段的废物收集.
主要方法:
- 一种细分收集方法模拟了医疗废物收集过程.
- 基于选择地点的最小包裹集群分析进行位置分配.
- 一个改进的非主导排序基因算法II (NSGA-II) 对于帕雷托最佳路线解决方案.
主要成果:
- 在稳定的废物生产下,改进的NSGA-II算法将总成本降低了高达13.94%,公里数降低了7.17%.
- 在大量废弃物增加期间,成本,里程和风险分别下降了9.50%,10.35%和2.03%.
- 该算法在两个场景中都提高了6%以上的全负载率,并且比传统的遗传算法更快地趋同.
结论:
- 提议的优化方法有效地解决了传染性医疗废物运输的挑战.
- 改进的NSGA-II算法在解决复杂的医疗废弃物路由问题上优于传统方法.
- 这种方法为高效和成本效益的医疗废物管理提供了可行的解决方案.
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