摘要
为提高重载铁路应急救援响应能力,构建风险评估云模型以确定事故易发区段,采用蒙特卡洛法生成事故场景。设计双目标物资调度模型,优化物资调度方案,采用非支配排序遗传算法(NSGA-Ⅱ)求解最优解。在保持站点不变、确保物资总量不变的情况下,提出匹配线路风险特性的救援物资储备优化方案。研究结果表明:优化后一级响应调度总距离平均缩减31.28%,二级响应缩减46.80%,表明优化后的储备方案能有效缩短响应时间和提高救援效率。研究结果可为重载铁路物资分布与调度提供理论指导。
To improve the emergency response capability of heavy-haul railway,a risk assessment cloud model was constructed to identify the accident-prone sections,and the accident scenes were generated using Monte Carlo method.A dual-objective materials dispatching model was designed to optimize the materials dispatching scheme,and the non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)was used to solve the optimal solution.While keeping the stations and total amount of materials unchanged,an optimized scheme of rescue materials reserve matching the risk characteristics of the railway line was proposed.The results show that after optimization,the total dispatching distance of first-level response is reduced by 31.28%on average,and that of second-level response is reduced by 46.80%,which indicate that the optimized reserve scheme can effectively shorten the response time and improve the rescue efficiency.The research results can provide theoretical guidance for the materials distribution and scheduling of heavy-haul railways.
作者
王剑飞
魏祎璇
汪澍
张海东
李树昆
金龙哲
丁天祺
WANG Jianfei;WEI Yixuan;WANG Shu;ZHANG Haidong;LI Shukun;JIN Longzhe;DING Tianqi(Shuohuang Railway Development Limited Liability Company,Beijing 100089,China;Research Institute of Macro-safety Science,University of Science and Technology Beijing,Beijing 100083,China;Beijing Chaoyang District National Defense Mobilization Office,Beijing 100020,China)
出处
《中国安全生产科学技术》
CAS
CSCD
北大核心
2024年第6期197-203,共7页
Journal of Safety Science and Technology
基金
北京市自然科学基金项目(9232023)。
关键词
重载铁路
物资调度
云模型
非支配排序遗传算法
heavy-haul railway
materials dispatching
cloud model
non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)
