One of the most critical problems in managing the car manufacturing factories' final assembly line is Car Sequencing Problem (CSP). The optimal permutation of car models is determined in a mixed model assembly line by solving this problem. In real-world cases, the unforeseen occurrence of disturbances like shortage or delay in feeding required parts to the assembly line cause to stir up an initially planned sequence. In this situation, the car resequencing problem is another challenge that should be solved. This study treats the car resequencing problem with an intermediate buffer before the final assembly line to rearrange the given initial sequence. Two objective functions are considered: (1) minimizing the ratio constraint violations (definitive objective of the car sequencing problem), and (2) minimizing work in process that remained in painted body storage (PBS) buffer. For this problem, a mathematical model as MIP is developed. Since this problem is discussed as intensely NP-hard, a new hybrid algorithm is proposed based on NSGAII and VNS to solve the medium and large scales. The numerical experiments are used according to sample problems in CSP Lib. to run the mathematical model and evaluate the developed approach's performance. The computational results show that the proposed method has a good effect on minimizing two objective functions in solving the medium and large-sized problems.