中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (12): 152-157.doi: 10.16265/j.cnki.issn1003-3033.2019.12.024

• 公共安全 • 上一篇    下一篇

应急救援物资多式联运路径优化

刘松1,2, 邵毅明**2 教授, 彭勇2 教授, 肖云鹏2   

  1. 1 山地城市交通系统与安全重庆市重点实验室,重庆 400074;
    2 重庆交通大学 交通运输学院,重庆 400074
  • 收稿日期:2019-09-11 修回日期:2019-11-10 出版日期:2019-12-28 发布日期:2020-11-24
  • 通讯作者: ** 邵毅明(1955—),男,重庆人,博士,教授,博士生导师,主要从事交通运输工程方面的研究。E-mail:sym@cqjtu.edu.cn。
  • 作者简介:刘 松 (1986—),男,重庆人,博士,主要从事交通运输规划与管理方面的工作。E-mail:515044261@qq.com。
  • 基金资助:
    国家自然科学基金资助(61803057);教育部人文社会科学研究规划基金资助(17YJA630079);山地城市交通系统与安全重庆市重点实验室基金资助(2018TSSMC04);重庆市社会科学规划项目(2019YBGL049)。

Multi-modal transport route optimization of emergency relief materials

LIU Song1,2, SHAO Yiming2, PENG Yong2, XIAO Yunpeng2   

  1. 1 Chongqing Key Lab of Traffic System & Safety in Mountain Cities, Chongqing 400074, China;
    2 School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2019-09-11 Revised:2019-11-10 Online:2019-12-28 Published:2020-11-24

摘要: 为将应急救援物资在最短时间内运抵受灾点,解决由公路、铁路、直升机等组成的应急救援物资多式联运路径优化问题,结合应急救援物资多式联运网络的实际情况,首先综合考虑运输时间的时变性、铁路发班时间限制,以及受天气等因素影响,导致直升机会有禁止飞行时段的特点,构建时变网络下的应急救援物资多式联运路径优化模型;然后设计蚁群算法;最后进行算例分析。研究结果表明:通过该模型和算法,可根据决策者的要求快速地选出将应急救援物资最快运抵受灾点的运输方案,可为决策者提供决策支持。

关键词: 应急救援物资, 多式联运, 路径优化, 蚁群算法, 单目标规划模型

Abstract: This research is conducted for the sake of optimizing multi-modal transport routes of emergency relief materials, highway, railway and airway, so as to transport them to disaster-stricken areas in the shortest time. In light of actual situation of multi-modal transport network, firstly, an optimization model of it under time-varying network was constructed with factors taken into consideration, like variation of transshipment time, time limit of railway dispatch, and prohibition time of flight due to weather conditions. Then, an ant colony algorithm was designed. Finally, a case study was carried out. The results show that this model and algorithm can quickly select a transportation plan that will deliver emergency relief materials to disaster-stricken areas in the shortest possible time according to requirements of decision-makers, thus providing necessary support for them.

Key words: emergency relief materials, multimodal transportation, route optimization, ant colony algorithm, single objective programming model

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