考虑客户分类的随机时间车辆路径优化模型与算法.

For the vehicle routing problem with time window, stochastic travel and service time, and customer classification, this paper constructed a chance constrained programming model, which considered two class customers (ordinary customers and priority customers) and adopted the chance constraint to guarantee the punctual service possibility of priority customers. Meanwhile, this paper designed a variable neighborhood iterated local search algorithm to solve the model, and proposed a minimum waiting time heuristic rule to generate initial solution. Based on Solomon benchmarks, it conducted series of simulation experiments. The results show that the initial solution generation method is valid, the given algorithm can get approximate optimal solutions for both of the deterministic and stochastic problems in a short time, and the customer ratio is positively relative to the number of vehicle usage . The results have a certain reference significance to solve the problem of low customer service level caused by the limited resources and uncertain factors. [ABSTRACT FROM AUTHOR]