In the urban logistics distribution industry, fluctuations in delivery time requirements directly disrupt the formulation of distribution plans, adversely affecting delivery efficiency and posing significant challenges to the effective determination of vehicle routing solutions. To address these challenges, a multi-strategy collaborative vehicle routing optimization algorithm considering dynamic delivery time requirements is proposed. Firstly, a dynamic vehicle routing optimization model is constructed, in which constraints are designed based on the impact of changes in customer time windows. The shortest travel distance, minimum waiting time, and least number of vehicles used are set as optimization objectives. Secondly, the types of changes in delivery time requirements are qualitatively analysed, and the intensity of such changes is quantitatively described. The chain impact factors of changing requirements are designed, and a comprehensive evaluation index for dynamic delivery time requirements is investigated. Finally, a strategy library for differential evolution algorithms is established. The priority of key optimization customers is identified based on the types of changes in delivery time requirements and comprehensive evaluation indicators of time requirements. And a multi-strategy collaborative vehicle routing optimization algorithm is developed. Experimental results demonstrate that the proposed method enables both qualitative analysis and quantitative characterization of changes in customer delivery time requirements, reduces the impact of delivery time requirement fluctuations on distribution plans significantly, and enhances the efficiency of vehicle routing optimization.