A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service
A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service
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DOI：
10.1007/s11067-013-9190-x
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发表时间：
2013-05
影响因子：
2.4
通讯作者：
Junlong Zhang;W. Lam;B. Chen
中科院分区：
文献类型：
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作者：
Junlong Zhang;W. Lam;B. Chen
准时发货对于准时生产和快速响应物流至关重要。由于旅行和服务时间的不确定性，无法确保车辆准时到达客户地点的概率。因此，在拥挤的道路网络中，准时运送货物对承运人来说是一项具有挑战性的工作。在本文中，这样的准时交货问题制定为一个随机车辆路径问题的行程和服务时间的不确定性下的软时间窗。提出了一种新的随机规划模型，以最小化承运人的总成本，同时保证最小的准时到达概率在每个客户位置。该模型的目的是在运营商的总成本和客户服务水平之间找到一个很好的权衡。为了解决该模型，迭代禁忌搜索启发式算法的发展，结合路径约简机制。提出了一种离散近似方法，用于生成存在时间窗的车辆到达时间分布。数值算例验证了模型和求解算法的适用性。
On-time shipment delivery is critical for just-in-time production and quick response logistics. Due to uncertainties in travel and service times, on-time arrival probability of vehicles at customer locations can not be ensured. Therefore, on-time shipment delivery is a challenging job for carriers in congested road networks. In this paper, such on-time shipment delivery problems are formulated as a stochastic vehicle routing problem with soft time windows under travel and service time uncertainties. A new stochastic programming model is proposed to minimize carrier’s total cost, while guaranteeing a minimum on-time arrival probability at each customer location. The aim of this model is to find a good trade-off between carrier’s total cost and customer service level. To solve the proposed model, an iterated tabu search heuristic algorithm was developed, incorporating a route reduction mechanism. A discrete approximation method is proposed for generating arrival time distributions of vehicles in the presence of time windows. Several numerical examples were conducted to demonstrate the applicability of the proposed model and solution algorithm.