恶劣天气因素下最优车辆路线调度路径选择

发布时间：2018-04-22 13:32

本文选题：最优车辆路线 + 车辆调度　；参考：《计算机仿真》2015年03期

【摘要】：考虑恶劣天气因素下的最优车辆路线调度关系到灾害环境下的货物运输效率。由于在较为恶劣的天气环境下,车辆路径的属性特征会发现不可预估的变化。上述属性变化无法通过设定权值进行程度的描述。利用传统算法进行车辆路线调度,没有充分考虑天气因素给车辆路径选择带来的影响。往往通过经验设定固定的影响权值,没有考虑对不同路径选择属性数据影响的差异性,调度过程缺陷明显。提出采用模拟退火遗传算法的最优车辆路线调度方法。依据相关理论构建车辆调度优化模型,结合在恶劣天气环境下,车辆行驶路径所需时间、交叉路口密度、通行能力等因素综合变化,根据模拟退火算法模拟差异化的天气影响因素,利用遗传算法求取模型最优解,实现考虑恶劣天气因素的最优车辆路线调度的路径选择。实验结果表明,利用改进算法进行车辆路线调度,能够有效的获取车辆当前的最佳路线,提高了车辆调度的效率。
[Abstract]:The optimal vehicle route scheduling considering severe weather factors is related to the freight transport efficiency in the disaster environment. Because of the bad weather environment, the attribute characteristics of the vehicle path will find unpredictable changes. The above attribute changes cannot be described by setting weights. The traditional algorithm for vehicle routing has not fully considered the influence of weather factors on vehicle routing. Usually the fixed influence weight is set by experience without considering the difference of the influence on different path selection attribute data and the defect of scheduling process is obvious. An optimal vehicle route scheduling method using simulated annealing genetic algorithm is proposed. According to the relevant theories, the vehicle scheduling optimization model is constructed, and the vehicle route time, intersection density, traffic capacity and other factors are comprehensively changed under the bad weather environment. According to the simulated annealing algorithm to simulate the different weather factors, the genetic algorithm is used to obtain the optimal solution of the model, and the route selection of the optimal vehicle route scheduling considering the bad weather factors is realized. The experimental results show that the improved algorithm can effectively obtain the best route of vehicle and improve the efficiency of vehicle scheduling.
【作者单位】：河南工业大学信息科学与工程学院;
【基金】：国家自然科学基金资助项目(61202099) 河南省科技厅科技攻关项目(122102110107)
【分类号】：U492.22;TP301.6

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