行驶受扰延迟下配送车辆调度的干扰管理决策模型

针对行驶受扰延迟下配送车辆的调度问题,提出了基于多相量子粒子群算法的两阶段干扰管理决策方法.首先以最小化用户时间窗偏离度和最小化配送成本为目标,建立了问题的数学模型;然后对车辆配送发生干扰事件可能采取的干扰管理模式进行了归纳和分类,并在选定模式基础上提出了用多相量子粒子群算法进行路线选择的方法;最后在Solomon算例的基础上通过实验仿真,对所提出方法的性能进行测试,并与全局重调度方法进行对比分析,验证了本文方法不仅达到了优化目标的目的,还满足了干扰管理的实用性要求.

Disruption management decision model for vehicle scheduling under traffic disruption delay

In order to solve the vehicle scheduling problem with traffic disruption delay, a two-stage disruption management method based on multi-phase quantum particle swarm optimization (MQPSO) is proposed. Firstly, a mathematical model of the problem is established to minimize the time window deviation and minimize the distribution cost. Next, the possible disruption management mode of distribution vehicles is summarized and classified and the route scheduling method is proposed on the basis of selected mode. At last, the simulation experiments are executed based on the Solomon example to test the performance of the proposed method. The effectiveness and practicability of the proposed method is verified through the comparison and analysis with rescheduling method.