Vehicle Routing Problems with Time Windows (VRPTW) is an important part of modern traffic control and a key part of transportation logistics. The goal is to reduce the total distance traveled or the number of vehicles utilized and to designate the routes for the vehicles. These issues have constantly gotten the attention of researchers and have become well-known problems in network optimization. This paper suggested a novel combination model that solves VRPTW using STPB Crossover in Genetic Algorithm and refined K-mean clustering. Experiments on the standard Solomon benchmark dataset were conducted to demonstrate the efficiency and reliability of VRPTW.