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Application of Hybrid Algorithm in Vehicle Routing Optimization Problem

机译:混合算法在车辆路径优化问题中的应用

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The problem of vehicle routing optimization is researched, to improve the efficiency of vehicle scheduling. With the increasing complexity of the traffic network, the vehicle will face the interference of accident and congestion, this situation is random and cannot be predicted. The traditional vehicle routing planning model lack of analysis of the interference risk, accurate model cannot be established, the vehicle scheduling operating efficiency is bad. In order to avoid these defects, the vehicle routing optimization method is proposed based on hybrid algorithm. According to the theory of traffic information feedback method, the feedback model of road information is established. It provides basis for vehicle routing optimization. The ant colony algorithm and extreme optimization algorithm are combined, the hybrid algorithm is obtained. According to the theory of hybrid algorithm, the vehicle routing optimization model is constructed, and related vehicle data is input in the model. The vehicle routing optimization processing is realized. The experiment results show that this algorithm can improve the scheduling efficiency, so as to meet the actual demand of traffic management.
机译:研究了车辆路径优化问题,以提高车辆调度效率。随着交通网络复杂性的增加,车辆将面临事故和交通拥堵的干扰,这种情况是随机的,无法预测。传统的车辆路径规划模型缺乏对干扰风险的分析,无法建立准确的模型,车辆调度运行效率差。为了避免这些缺陷,提出了一种基于混合算法的车辆路径优化方法。根据交通信息反馈方法的理论,建立了道路信息反馈模型。它为车辆路线优化提供了基础。结合蚁群算法和极限优化算法,得到了混合算法。根据混合算法理论,构造了车辆路径优化模型,并将相关的车辆数据输入模型中。实现了车辆路径优化处理。实验结果表明,该算法可以提高调度效率,满足交通管理的实际需求。

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