Abstract: To adapt the vehicle routing problem with fuzzy demands to the reality,by breaking vehicles'single-trip restrictions and introducing the time window preferences of customers,a Multi-trip Vehicle Routing Problem with Fuzzy Demands considering Time Window preference (MVRPFDTW) was researched.In pre-optimization phase with unknown demands,a pre-optimization model was presented to minimize the sum of logistic cost and time cost.In the model,the decision variable with multi-trip was set.Then the vehicle capacity constraint was calculated in a single-trip,the customer arrival time was computed in accumulative multi-trip,and the customer satisfaction was defined as the membership function of the arrival time.In real-time adjustment phase with known demands,a real-time adjustment strategy with expected adjustment cost was proposed based on the two principles namely advanced flexible return and unfixed plan return.Computational examples were used to test the validity of the pre-optimization model and the real-time adjustment strategy by using the population evolutionary algorithm and the stochastic simulation algorithm.

Key words: vehicle routing problem with fuzzy demands, multi-trip, time window preference, pre-optimization model, real-time adjustment strategy

摘要： 为使模糊需求车辆路径问题更贴近现实情况,考虑开放车辆行程限制和设置客户时间窗偏好,研究了带时间窗偏好的多行程模糊需求车辆路径问题。首先,在需求未明的预优化阶段,以物流成本和时间成本总和最小为目标,建立了预优化模型,其中决策变量增加了行程维度的表达、车辆容量约束按单行程核算、客户到达时间约束按多行程累加计算、客户满意度约束定义为到达时间隶属度函数;其次,在获知实际需求的实时调整阶段,基于提前柔性选择返回点和不完全局限和固定计划返回点两个原则,提出基于调整成本期望值的实时调整策略。最后,种群进化算法求解测试算例验证了预优化模型的有效性,随机模拟算法模拟实时场景验证了实时调整策略的有效性。

关键词: 模糊需求车辆路径问题, 多行程, 时间窗偏好, 预优化模型, 实时调整策略