一个多目标数学编程模型,用于P-envy问题 紧急医疗服务位置
Mohammad Khalilzadeh1, Arman Bahari2
1CENTRUM Católica Graduate Business School, Pontificia Universidad Católica del Perú, Lima, Peru.
Health services insights
|September 4, 2023
概括
本研究提出了一个最佳紧急医疗服务 (EMS) 位置的数学模型. 基因算法 (GA) 证明比模拟化 (SA) 更有效,最大限度地覆盖并最大限度地降低成本.
科学领域:
- 运营研究 运营研究
- 卫生系统管理管理卫生系统管理
- 公共卫生 公共卫生
背景情况:
- 有效的紧急医疗服务 (EMS) 对于在紧急情况下减轻风险至关重要.
- 优化EMS设施的位置是全球医疗保健系统面临的重大挑战.
- 在医疗保健规划中,平衡患者覆盖,建筑成本和服务可访问性至关重要.
研究的目的:
- 开发一个多目标的数学编程模型来定位和构建EMS.
- 为了最大限度地提高患者的覆盖率和生存概率,同时最大限度地降低EMS建设成本.
- 为需要紧急医疗服务的地区优化服务比率.
主要方法:
- 制定了一个多目标数学编程模型.
- 最小的P-envy算法适应了EMS的位置.
- 用基因算法 (GA) 和模拟化 (SA) 来解决NP-Hard问题.
- 塔古奇方法用于调整元启发算法参数.
主要成果:
- 通过解决实例问题来证明拟议模型的有效性.
- 基因算法 (GA) 在各种问题大小的解决方案质量方面超过了模拟炼 (SA) 算法.
- 与SA相比,GA在EMS的位置和构建方面提供了更有效的解决方案.
结论:
- 开发的数学模型有效地解决了EMS的位置挑战.
- 与SA相比,GA是一种优越的元启发算法,可以优化EMS的配置.
- 这些发现支持改善紧急医疗服务的规划和资源配置.
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