中文摘要：

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。

英文摘要：

The optimal vehicle routing scheduling considering bad weather factors is related to cargo transportation efficiency under the disaster environment. An optimal vehicle routing scheduling method using simulated annealing genetic algorithm was proposed in the paper. On the basis of related theory,the optimization model of vehicle scheduling was constructed. Combined with environment of bad weather,required time of vehicle traveling route,intersection density,traffic capacity and other factors,according to the simulated annealing algorithm,different weather influence factors can be simulated. By using genetic algorithm,the optimum solution of the model was obtained,to realize the optimal path selection of vehicle routing scheduling by taking into account the bad weather factors. The experimental results show that,using the improved algorithm for vehicle routing scheduling,can effectively obtain the current optimal route of vehicle and improve the efficiency of vehicle scheduling.