基于人工鱼群算法的出租车智能调度

发布时间：2018-04-12 12:24

本文选题：智能交通 + 全局优化　；参考：《系统工程理论与实践》2017年11期

【摘要】：出租车以其方便、快捷、舒适等特点成为城市公共交通工具的重要补充,但是当前出租车资源普遍存在着分布不合理、空载率高、营运效率低下等问题.本文运用群智能的思想,提出基于人工鱼群算法的出租车智能调度方法,以实现对出租车资源的全局调度与合理分配.论文提出标准人工鱼群算法中的觅食函数、聚群函数和追尾函数的改进方案以及当前最优状态阈值限定的优化策略,使得改进算法具有全局寻找最优解的良好搜索能力.同时通过模拟实验分析视野、尝试次数、拥挤度因子、迭代次数和游动步长等参数对出租车调度算法寻优能力的影响.研究成果为城市出租车资源得到科学合理规划以及全局优化分配提供新思路和依据.
[Abstract]:Taxi has become an important supplement to urban public transportation because of its convenient, fast and comfortable characteristics. However, there are some problems such as unreasonable distribution of taxi resources, high no-load rate and low operating efficiency.This paper presents an intelligent taxi scheduling method based on artificial fish swarm algorithm with the idea of swarm intelligence, so as to realize the global scheduling and rational allocation of taxi resources.In this paper, the feeding function, clustering function and rear-end function of the standard artificial fish swarm algorithm are improved, and the optimization strategy of the threshold limit of the current optimal state is proposed, which makes the improved algorithm have a good ability to search for the optimal solution globally.At the same time, the effects of parameters such as visual field, number of attempts, congestion factor, iteration number and walk length on the optimization ability of taxi scheduling algorithm are analyzed by simulation experiments.The research results provide a new idea and basis for the scientific and rational planning and global optimal allocation of urban taxi resources.
【作者单位】：武汉大学国际软件学院;巴黎高科国立高等电信学校计算机科学与网络系;东京大学空间情报科学研究中心;
【基金】：苏州科技局国际科技合作计划(SH201213)~~
【分类号】：TP18;U492.22

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