School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.
J Hazard Mater. 2013 Feb 15;246-247:234-44. doi: 10.1016/j.jhazmat.2012.11.009. Epub 2012 Nov 10.
Nuclear emergency evacuation is important to prevent radioactive harms by hazardous materials and to limit the accidents' consequences; however, uncertainties are involved in the components and processes of such a management system. In the study, an interval-parameter joint-probabilistic integer programming (IJIP) method is developed for emergency evacuation management under uncertainties. Optimization techniques of interval-parameter programming (IPP) and joint-probabilistic constrained (JPC) programming are incorporated into an integer linear programming framework, so that the approach can deal with uncertainties expressed as joint probability and interval values. The IJIP method can schedule the optimal routes to guarantee the maximum population evacuated away from the effected zone during a finite time. Furthermore, it can also facilitate post optimization analysis to enhance robustness in controlling system violation risk imposed on the joint-probabilistic constraints. The developed method has been applied to a case study of nuclear emergency management; meanwhile, a number of scenarios under different system conditions have been analyzed. It is indicated that the solutions are useful for evacuation management practices. The result of the IJIP method can not only help to raise the capability of disaster responses in a systematic manner, but also provide an insight into complex relationships among evacuation planning, resources utilizations, policy requirements and system risks.
核紧急事件疏散对于防止危险物质造成放射性危害和限制事故后果非常重要；然而，在这样的管理系统的组成部分和过程中存在不确定性。在研究中，开发了一种区间参数联合概率整数规划（IJIP）方法，用于不确定性下的紧急疏散管理。区间参数规划（IPP）和联合概率约束（JPC）规划的优化技术被纳入整数线性规划框架中，使得该方法能够处理以联合概率和区间值表示的不确定性。IJIP 方法可以安排最佳路线，以确保在有限的时间内将最大数量的人口从受影响区域疏散出去。此外，它还可以促进后续的优化分析，以增强对联合概率约束下的系统违规风险的控制能力。所开发的方法已应用于核紧急事件管理的案例研究，并分析了不同系统条件下的多个场景。结果表明，这些解决方案对疏散管理实践很有用。IJIP 方法的结果不仅有助于系统地提高灾害应对能力，还可以深入了解疏散规划、资源利用、政策要求和系统风险之间的复杂关系。
