Abstract: To address the increasing city distribution demands constrained by traffic congestion, vehicle waiting and discrete scheduling strategy are introduced by analyzing the effect of time-dependent on cost and CO2 emissions, and time-dependent vehicle routing and discrete scheduling problem is proposed. To solve this significant problem, a hybrid evolutionary algorithm is designed by combining genetic algorithm and local search in which randomly mutation is replace by positive local search mechanisms. In this algorithm, initial solution generate procedure, variable probability crossover and multiple local search strategies are designed to improve the quality and efficiency. The validity of designed algorithm and the proposed model is finally verified by computational experiments.

Key words: time-independent, vehicle routing-scheduling, CO2 emissions, hybrid evolutionary algorithm

摘要： 针对交通拥挤环境下日益增长的城市配送需求，通过分析时序依赖对成本和碳排放的影响，引入车辆在节点等待和离散调度策略，研究基于时序依赖的低碳城市配送车辆路径与离散调度问题。为求解该问题，设计基于遗传算法与局部搜索相结合的混合进化搜索算法对模型求解，用积极的局部搜索机制替代随机的变异操作，并通过可行解构造算法、变概率交叉和多种局部搜索策略来提高算法求解质量和求解效率。通过对比仿真实验对算法和模型的有效性进行了验证。

关键词: 时序依赖, 车辆路径-发车调度, 碳排放, 混合进化算法