This paper discusses a reentrant hybrid flowshop scheduling problem with the objective of minimizing total weighted completion time. An integer programming model is then developed. The scheduling coding scheme of two-dimensional matrix is designed based on the features of the model. Then, the initial job processing sequence is obtained using NEH heuristic in order to generate the initial scheduling population with high quality. The self-adaptive adjustment strategy of the genetic parameters in improved genetic algorithm(IGA) is proposed to avoid the early maturing of the algorithm and expands the search space. Thus the NEH-IGA algorithm is provided combined with the above improvement. Simulation experiments are perfomed on different sized problems respectively using the traditional GA, IGA based on the self-adaptive adjustment of genetic parameters, NEH heuristic and NEH-IGA. Numerical results show that the introdution of NEH heuristic and the self-adaptive adjustment strategy of genetic parameters can improve the solution ability of the original GA effectively. The NEH-IGA has more advantage in terms of solving the RHFS-TWC problem.