| To meet customer needs as much as possible is an important means of improving the service quality and enhancing market competitiveness for every logistic enterprise. But in reality, customers may not be able to get to the given place at the given time as a result of accidental events. Therefore, they have to change their time windows of logistic services even if the delivery vehicles are running. It is a great challenge for logistic enterprises that the customer time window changes are not only inevitable but also hard to predict. Although all logistic enterprises wish to meet customers’demands, they have to consider their logistic capacities and system disruptions. They also have to answer customers based on the considerations of system disruptions and customers’satisfactions.This paper focuses on the disruption management problem of customer time window changes. A disruption management model for customer time window changes is studied and its algorithm is designed, which are proved by application instances. This paper will present theory and methodology supports for logistic enterprises to solve the problems of customer time window changes. The main research work is summarized as follows:(1) Problem analysisA typical disruption management process of logistic enterprises is analyzed for customer time window changes in distribution. The process is concluded as a multi-stage discussion procedure between customers and logistic enterprises. Two problems that occurred in the procedure are discussed. The first problem is the changing of vehicle routes when customers have changed their time windows in order to minimize the system disruption. The second problem is to recommend a feasible time window which is nearest to the changed time window of a customer when the logistic enterprise can not accept the system disruption. The analysis of the disruption management problem forms the basis of modeling and solving the problem.(2) Research on the disruption management model for customer time window changesThe disruption that the customer time window changes bring to the distribution system is measured by the three aspects of customers, vehicle drivers, and logistic enterprises. Two models are constructed:one is the vehicle route changing model after a customer time window changes, and the other is the new time window recommendation model. A multi-stage disruption management model for customer time window changes is made based on the above two models.(3) Research on the disruption management algorithm for customer time window changesA genetic algorithm is designed to solve the vehicle route changing model. In the algorithm, a two-dimension chromosome structure and a fitness function that fits multi-objective decision model are presented. A heuristic algorithm is also presented to solve the model. The heuristic iteratively assigns each disrupted customer to its old vehicle, other running vehicles, or an idle vehicle. To solve the new time window recommendation model, the sequence of the non-served customers of the disrupted vehicle is changed; and the best one will be chosen by the heuristic algorithm according to the system disruption. The customer time window of the best service sequence will be relaxed in order to obtain a recommended time window.(4) Application research on the disruption management problem for customer time window changes in distributionBenchmark instances are used to test the validities of the algorithms. The presented disruption management model and algorithm are also used to deal with the customer time window changes in the express and distribution of JingDong Logistics in order to test their validities.This paper contributes to the exploration of the disruption management problem for customer time window changes in distribution. It helps to increase the instantaneity and the rationality of the disruption management in distribution and improve the old disruption management method in most logistic enterprises. The results should enhance the robustness of the disruption management system in distribution, and promote the theory and application research of disruption management towards the flexible interactions between logistic enterprises and customers. |
