中文摘要：

现实中，行驶在道路上的车辆由于车流量等因素导致车辆通过时间随着时间的变化而波动较大。因此，标准车辆路径问题中关于车辆在道路上的行驶速度或通过时间恒定的假设前提通常不能得到满足。以标准的带容量约束的车辆路径问题为基准，研究当道路的通过时间随着时间的变化而变化，并综合考虑行驶距离、行驶时间等多项目标下车队的最佳路线安排。为了求解所提出的扩展问题，设计了一个模拟退火与遗传算法相结合的多目标混合遗传算法，用于计算得到研究问题的最优Pareto集合。通过对多个基准问题的算法测试，验证了算法的有效性。

英文摘要：

In real world, traveling time of vehicles on the same road varies greatly at different time due to the traffic status. Thus the assumption of constant speed of vehicle on the road in the standard vehicle routing problem does not hold. This paper studies an extended capacitated vehicle routing problem, where the traveling time of vehicles between two locations is time-dependent. Furthermore the objectives of the problem include the total traveling distance of all vehicles, the total traveling time of vehicles, and the trad-off between the traveling distance and traveling time of each vehicle. To solve this complicated problem, a hybrid genetic~simulated annealing algorithm is proposed to find the Pareto-optimal solutions. Several benchmark problems are used to demonstrate the feasibility and effectiveness of the algorithm.