Real-time city distribution strategies are highly dependent on dynamic environments, requiring timely responses to changes of demand and environment due to various dynamic events that take place in the distribution system. A dynamic vehicle routing model based on a dynamic pick-up and delivery problem considering multiple dynamic events in a real-world environment (DPDP-MDE) was established, considering the influence of four kinds of real-time information on vehicle routing and vehicle scheduling, including new requests arriving gradually, old requests being modified or canceled, traffic congestion and vehicle breakdowns. A dynamic algorithm framework is designed to solve this model. The execution rules and calculation rules of static subproblems within scheduled time horizon are given. The constructive heuristic algorithm is used to generate the initial feasible solution for the exact static subproblems. Two intelligent optimization algorithms, tabu search algorithm and adaptive large-scale neighborhood search algorithm, are adopted to improve the quality of those initial feasible solution. The dynamic insertion method is adopted to solve the synchronization problem of unfixed requests and new requests when updating the routing. Experimental results show that the model and dynamic algorithm framework proposed can effectively solve the dynamic pick-up and delivery problem with time windows (DPDP-TW).