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在分析电动汽车加电站运营模式的基础上,根据电动汽车加电站需求动态变化的特点,建立了加电站电池配送路径问题的动态车辆调度模型.利用自适应准则改进遗传算法,构造了自适应遗传算法;针对动态车辆调度问题实时性强的特点,设计了“初始化路径制定+实时动态调度”的两阶段求解策略,通过信息更新插入动态需求加电站,对已产生的计划路径进行局部优化调整,仿真计算结果验证了模型和算法的有效性.
Based on the analysis of the operating mode of EV station and based on the dynamic demand of EV station, a dynamic vehicle scheduling model of battery delivery path in station was established. The adaptive genetic algorithm was used to improve the genetic algorithm and construct adaptive genetic Algorithm. Aiming at the strong real-time performance of dynamic vehicle scheduling problem, a two-stage solution strategy of “initial path planning + real-time dynamic scheduling” is designed. Through the information update, a dynamic demand power station is inserted to locally optimize the planned path Adjustment and simulation results verify the effectiveness of the model and algorithm.