| 基于改进蚁群算法的车辆路径优化 |
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| 引用本文： | 曹洁,屈展.基于改进蚁群算法的车辆路径优化[J].电气自动化,2010,32(1):38-40. |
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| 作者姓名： | 曹洁 屈展 |
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| 作者单位： | 兰州理工大学电气工程与信息工程学院,兰州,730050 |
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| 基金项目： | 引进国际先进农业科技计划(948计划) |
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| 摘 要： | 针对基本蚁群算法易陷于局部最优解及道路交通流易产生拥塞等缺陷，提出了一种改进蚁群算法。结合实时交通信息，以时间最短建立了动态路径规划的目标转换模型，应用改进蚁群算法求解车辆最短路径，对于求解过程中出现局部最优解，引入了随机蚂蚁这一概念，同时基于Greenshields模型处理了正反馈以及个体最优策略造成的拥塞现象。
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| 关 键 词： | 路径规划 蚁群算法 动态路径规划 随机蚂蚁 拥塞 |
Vehicle Routing Optimization Based on Improved Ant Colony Algorithm |
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| Cao Jie,Qu Zhan.Vehicle Routing Optimization Based on Improved Ant Colony Algorithm[J].Electrical Automation,2010,32(1):38-40. |
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| Authors: | Cao Jie Qu Zhan |
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| Affiliation: | ( Lanzhou University of Technology, Lanzhou Gansu 730050, China) Cao Jie Qu Zhan |
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| Abstract: | In this paper an improved ant colony algorithm is proposed to overcome the shortcomings of the basic ant colony algorithm, such as the traffic congestion of road traffic flow, being prone to fall into partial optimum and so on. A dynamic route planning target conversion model is established with real-time traffic information and the shortest-time path. An improved ant colony algorithm is applied to fred out the optimum path based on the model in the shortest possible time according to the real-time traffic information. When the local optimum is appeared, a stochastic ant concept is introduced, and Greenshields model is used to deal with positive feedback and congestion caused by local optimum policy. |
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| Keywords: | route planning ant colony algorithm dynamic route planning stochastic ant congestion |
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