This paper explores the application of the Monarch Butterfly Optimization (MBO) algorithm to address the Vehicle Routing Problem with Time Windows and Delivery Priorities (VRPTWDP). The VRPTWDP is a challenging combinatorial optimization problem with significant real-world implications in logistics and transportation. In this study, we delve into the mechanics of the MBO algorithm, leveraging its swarm intelligence characteristics to efficiently solve this intricate problem. Through comprehensive experimentation and analysis, author demonstrates the algorithm's effectiveness in optimizing vehicle routes with varying constraints and priorities. The findings present promising results, paving the way for further research and practical implementation in swarm intelligence, transportation and logistics management.