The classification, collection, and treatment of municipal solid waste contribute to improving the urban living environment. Different categories of waste have varying characteristics and collection time-frames, and the daily production of each type of waste differs, resulting in varying collection frequencies. Ensuring the timely removal of waste from each collection point has gradually become a key aspect of municipal solid waste management. This study approaches the issue of municipal solid waste collection and transportation from the perspective of timeliness. Based on the timeliness requirements for different waste categories and corresponding waste generation volumes in various collection point, a mathematical model is established to address the vehicle routing problem under determined demand. The model is solved using a genetic algorithm, with a mutation probability introduced to prevent the algorithm from falling into a local optimum in the later stages of iteration, thereby enhancing its global search capability. This enables a reasonable determination of collection stations, times, schedules, vehicle assignments, and routes. Finally, the study further analyzes the impact of various parameters on the optimal solution and vehicle routing, validating the effectiveness of the results. And it may provide a theoretical reference for urban waste collection planning.