Routing optimization of cross-regional emergency rescue considering differentiated disaster impacts

被引:0
|
作者
Zhu L. [1 ]
Gu J. [1 ]
Ma Z. [1 ]
Xu Y.-S. [1 ]
机构
[1] School of Economics and Management, Nanjing University of Information Science & Technology, Nanjing
来源
Kongzhi yu Juece/Control and Decision | 2017年 / 32卷 / 05期
关键词
Ant colony algorithm; Cross-region; Emergency; Heterogeneity; Vehicle routing problem;
D O I
10.13195/j.kzyjc.2016.0157
中图分类号
学科分类号
摘要
Focusing on the various severity of the victims' injuries appeared in different disaster areas, using the diverse final due date or sufferable duration that the casualties can stick to be rescued, we characterize different disaster area impacts and discuss the cross-regional emergency vehicle routing problem with time window. Firstly, a vehicle routing optimization model with minimizing the traveling time is developed, and a modified ant colony algorithm is designed to solve this model. Then, the impacts of differentiated disaster on the cross-regional emergency rescue routing optimization are discussed. Finally, taking decision-makers' risk attitude as an example, we perform the simulation analysis and demonstrate the effects of key parameters. The results provide some suggestions for establishing an effective emergency management system. © 2017, Editorial Office of Control and Decision. All right reserved.
引用
收藏
页码:879 / 884
页数:5
相关论文
共 13 条
  • [11] Yuan Y., Wang D., Path selection model and algorithm for emergency logistics management, Computers & Industrial Engineering, 56, 3, pp. 1081-1094, (2009)
  • [12] Dorigo M., Gambardella L.M., Ant colony system: A cooperative learning approach to the traveling salesman problem, IEEE Trans on Evolutionary Computation, 1, 1, pp. 53-66, (1997)
  • [13] Wang Z., Uncertainty index based consistency measurement and priority generation with interval probabilities in the analytic hierarchy process, Computers & Industrial Engineering, 83, 5, pp. 252-260, (2015)