Vertex cover is a famous NPhard problem and has important applications in many fields such as communication networks, bioinformatics and so on. Current researches mainly study it from the aspects of heuristic algorithms or approximate algorithms, which cannot achieve global optimization. Kernelization is a new approach dealing with hard problems. We propose an algorithm framework combining heuristic operation and kernelization operation and apply the kernelization technique to optimizing heuristic vertex cover algorithms. Kernelization operation identifies the set of vertices belonging to some optimal solutions, while heuristic operation changes the network topology, which guarantees that the kernelization operation can be executed successfully in the next loop.The optimization is achieved by interleaving the kernelization operation and heuristic operation. Simulation results show that the proposed algorithm can achieve various degrees of optimization in different networks. Moreover, it can obtain the optimal solution in almost all sparse network instances.