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中国管理科学 ›› 2019, Vol. 27 ›› Issue (4): 190-197.doi: 10.16381/j.cnki.issn1003-207x.2019.04.018

• 论文 • 上一篇    下一篇

社区应急疏散动态协作调度优化研究

张佰尚1,2, 范刚龙1, 唐攀3, 贾玉奎2, 尹如法4   

  1. 1. 洛阳师范学院河南省电子商务大数据处理与分析重点实验室, 河南 洛阳 471934;
    2. 国家市场监督管理总局发展研究中心, 北京 100088;
    3. 暨南大学应急管理研究中心, 广东 广州 510632;
    4. 中国建筑科学研究院有限公司建筑机械化研究分院, 河北 廊坊 065000
  • 收稿日期:2017-06-30 修回日期:2018-03-16 出版日期:2019-04-20 发布日期:2019-06-12
  • 通讯作者: 张佰尚(1984-),男(汉族),河南安阳人,洛阳师范学院讲师,博士,国家市场监督管理总局发展研究中心助理研究员,研究方向:电子商务、应急管理,E-mail:16819966@163.com. E-mail:16819966@163.com
  • 基金资助:

    国家自然科学基金资助项目(71774068)

Research on the Dynamic Collaborative Scheduling Optimization for Community Evacuation

ZHANG Bai-shang1,2, FAN Gang-long1, TAN Pang3, JIA Yu-kui2, YIN Ru-fa4   

  1. 1. Key Laboratory of Henan Province for E-commerce Big Data Processing and Analysis, Luoyang Normal University, Luoyang 471934, China;
    2. Development Research Center of State Administration for Market Regulation of the People's Republic of China, Beijing, 100088, China;
    3. Emergency Management Research Center, Jinan University, Guangzhou 510632, China;
    4. Institute of Building Mechanization, China Academy of Building Research Co. Ltd, Langfang 065000, China
  • Received:2017-06-30 Revised:2018-03-16 Online:2019-04-20 Published:2019-06-12

摘要: 针对灾民数量和路网通行时间的动态性以及灾民疏散反应系数的随机性,本文提出了社区应急疏散协作调度优化流程,并以疏散灾民数量最大化和疏散成本最小化为目标,构建了社区应急疏散多种运输方式协作调度优化模型,并给出了求解该模型的改进多目标遗传算法。然后,论文使用Tansmodeler模拟社区应急疏散协作调度优化过程,加载疏散灾民动态需求和历史出行时间表,并对模型和算法进行验证。结果表明,该模型和算法可以在有效刻画疏散灾民数量和路网通行时间的基础上,为不同时刻的交通工具配置及疏散路径选取提供决策。

关键词: 交通运输系统工程, 动态协作调度优化, 仿真, S反应曲线, 多目标机会约束规划

Abstract: In consideration of the temporal dynamics of evacuees and road network traffic time and the randomness of evacuation response parameter, the collaborative scheduling optimization process of community emergency evacuation was proposed. At the same time, the coordination scheduling optimization model with varieties of transportation tools was constructed and the multi-object algorithm was designed for community evacuation, which aims to hit the targets of evacuated victims maximizing and evacuation cost minimizing. Then, the collaborative scheduling optimization process of community emergency evacuation was simulated and tested with Tansmodeler software platform, during which the dynamic evacuees demand and road network traveling time table were loaded in real time. Results show that there are different evacuees demand and road network transit-time and the proposed process, model and algorithm can provide decision-making in real time for the planning of transportation tools and the selection of evacuation routs according to dynamic evacuee quantity and road network transit-time.

Key words: engineering of communications and transportation system, dynamic collaborative scheduling optimization, simulation, s-curve, multi-object chance-constrained programming

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