Management decision model for dynamic vehicle scheduling under disruption delay

The purpose of this study was to investigate the traffic disruption delay, it is a big vehicle scheduling problem in VRP (vehicle routing problem). In this paper an improved ant colony algorithm is proposed which is on the basis of two-stage disruption management method. Firstly, Quantum H Gate is used to replace traditional quantum revolving door to update the ant colony. Next, the possible disruption management mode of distribution vehicles is summarized and the route scheduling method is designed on the basis of selected mode. The results obtained in this study include the performance of the proposed method, the classical Solomon example is involved in this paper. Findings show that the discrimination of the proposed MQACA (multi-phases quantum ant colony algorithm) is higher than conventional existing methods and the results are reasonable.