关键词: 城市物流配送, 随机需求有时间窗车辆路径问题, 补救策略, 混合进化算法

Abstract: Based on the characteristics of uncertainty and timeliness of customer demands in urban logistics, this paper considers a problem of vehicle routing with stochastic demands and time windows, and as well as three remediation strategies with different information scheduling levels on condition of the delivery failure. A chance constrained and mixed integer programming mathematical model is constructed and transformed into an equivalent deterministic one for solving. An improved hybrid evolutionary algorithm with multiple operators is proposed to solve the model, and the superiority of the algorithm is verified by an example. Besides, the sensitivity of the model parameters and the risk cost under the three remediation strategies are analyzed. The results show that the real time feedback and dispatching strategy can decrease the risk costs of time constraint as  much as possible and the economic advantage of reducing the distribution distance is obvious.

Key words: urban logistics, Vehicle Routing Problem with Stochastic Demands and Time Windows（VRPSDTW） , remediation strategies, hybrid evolutionary algorithm