针对时变路网下多中心混合车队联合配送车辆路径问题，综合考虑多配送中心开放、燃油车及电动车联合配送、车辆行驶速度连续变化等因素的影响，构建以车辆固定成本、运营成本和时间窗惩罚成本之和最小为目标的优化模型。根据问题特征，设计混合启发式算法进行求解，算法中采用K-means聚类方法生成初始种群，然后用变邻域搜索算法进行搜索优化，提升算法的求解性能。设计多组实验对本文算法进行对比分析，验证了算法的有效性。研究成果丰富了时变路网和混合车队车辆路径问题的相关理论研究，为运输企业制定合理的运输方案提供了理论依据。

Aiming at the vehicle routing problem of joint distribution of multi-center hybrid fleet under time-varying road network, considering the opening of multi distribution centers, joint distribution of fuel vehicles and electric vehicles, continuous change of vehicle speed and other factors, an optimization model aiming at minimizing the sum of vehicle fixed cost, operation cost and time window penalty cost was constructed. According to the characteristics of the problem, a hybrid heuristic algorithm was designed to solve it. In the algorithm, the K-means clustering method was used to generate the initial population, and then the variable neighborhood search algorithm was used for search optimization to improve the solution performance of the algorithm. Several groups of experiments were designed to compare and analyze the algorithms, the effectiveness of the algorithm was verified. The research results enrich the relevant theoretical research on timevarying road network and hybrid fleet vehicle routing problem, and provide a theoretical basis for transportation enterprises to formulate reasonable transportation schemes.