基于改进蚁群算法的城市内涝救援路径优化

doi:10.11772/j.issn.1001-9081.2014.07.2103

计算机应用 ›› 2014, Vol. 34 ›› Issue (7): 2103-2106.DOI: 10.11772/j.issn.1001-9081.2014.07.2103

基于改进蚁群算法的城市内涝救援路径优化

姜金贵¹,²,张鹏飞¹,²

1. 哈尔滨工程大学经济管理学院，哈尔滨 150001；
2. 哈尔滨工程大学灾难与危机管理研究所，哈尔滨 150001

收稿日期:2014-01-17 修回日期:2014-02-24 出版日期:2014-07-01 发布日期:2014-08-01
通讯作者: 姜金贵
作者简介:姜金贵(1980-)，男，黑龙江哈尔滨人，副教授，博士，主要研究方向：危机响应与信息系统；张鹏飞(1988-)，男，山东潍坊人，硕士研究生，主要研究方向：危机响应与信息系统。
基金资助:
国家自然科学基金资助项目;教育部人文社会科学青年基金;黑龙江省教育厅人文社会科学项目;中央高校基本科研业务费专项资金资助项目

Route optimization of unban waterlogging rescue based on improved ant colony optimization

JIANG Jingui¹,²,ZHANG Pengfei¹,²

1. Research Institute of Disaster and Crisis Management, Harbin Engineering University, Harbin Heilongjiang 150001, China
2. School of Economics and Management, Harbin Engineering University, Harbin Heilongjiang 150001, China；

Received:2014-01-17 Revised:2014-02-24 Online:2014-07-01 Published:2014-08-01
Contact: JIANG Jingui

摘要/Abstract

摘要：

城市内涝灾害发生时，科学调配救援资源能够有效提升城市应急救援的效率，最大限度降低灾害损失。针对城市线路受到地形、路况、内涝积水等因素影响的情况，引入连通系数和畅通系数，从而更好反映城市线路及灾情实际。鉴于蚁群算法收敛速度慢、容易陷入局部最优的缺点，通过随机选择受灾点、引入信息素更新策略改进了蚁群算法，并应用其对内涝救援路径优化模型进行求解。实证分析表明改进蚁群算法对城市内涝救援路径优化具有较好的求解效果。

Abstract:

When urban waterlogging disasters occur, the scientific deployment of rescue resources can improve the efficiency of urban emergency rescue, and minimize disaster losses. In view of the fact that urban routes are affected by terrain, road conditions and the seriousness of waterlogging, the authors introduced the connected coefficient and the unblocked coefficient, so as to better reflect the urban route conditions and waterlogging disaster. Considering that the ant colony algorithm has some disadvantages, such as slow convergence, easy to fall into local optimum, by randomly selecting the affected areas and introducing a pheromone update operator strategy the ant colony algorithm was improved, which is used to solve the route optimization model. Empirical analysis shows that the improved ant colony algorithm of solving urban waterlogging rescue route optimization has better result.

姜金贵张鹏飞. 基于改进蚁群算法的城市内涝救援路径优化[J]. 计算机应用, 2014, 34(7): 2103-2106.

JIANG Jingui ZHANG Pengfei. Route optimization of unban waterlogging rescue based on improved ant colony optimization[J]. Journal of Computer Applications, 2014, 34(7): 2103-2106.

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基于改进蚁群算法的城市内涝救援路径优化

Route optimization of unban waterlogging rescue based on improved ant colony optimization

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