一个双目标的强大优化模型,用于不确定性下的位置-运输,具有心理成本
Tingting Zhang1, Yanqiu Liu1, Zhongqi Peng1
1School of Management, Shenyang University of Technology, Shenyang, China.
PloS one
|January 12, 2026
概括
本研究介绍了地震救援物流的强大优化模型,平衡伤亡人数的不确定性和心理需求,以最大限度地降低伤害严重程度和心理成本,以便更好地应对紧急情况.
科学领域:
- 运营研究 运营研究
- 灾害管理 灾害管理
- 公共卫生 公共卫生
背景情况:
- 由于不可预测的伤亡人数和心理创伤,地震救援物流面临重大不确定性.
- 有效的应急响应需要将伤亡者的心理状况纳入救援策略.
研究的目的:
- 为最佳医疗设施位置和伤亡人员运输规划开发一个双目标强大的优化模型.
- 为了最大限度地减少总伤害严重性评分 (ISS) 和不确定性下的心理成本.
主要方法:
- 开发了一个三层级的救援链模型 (灾区,临时医院,综合医院).
- 强大的优化和[公式:参见文本]约束方法被用来解决双目标随机模型.
- 使用ISS和动态恶化率的伤亡分类被纳入.
主要成果:
- 伤亡人数的不确定性增加显著影响了总的ISS.
- 解决心理状况可以改善人道主义护理,但可能会降低救援效率.
- 优先考虑严重伤亡和扩大临时医院容量,提高救援效率.
结论:
- 强大的优化模型在大规模灾难场景中优于决定性模型.
- 决策者必须根据具体偏好,平衡人道主义护理与救援效率.
- 该模型为优化地震后情景中的医疗资源分配提供了一个框架.
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