In the automobile engine flow shop (AEFS), the equipment has more chance to work for a long time, so the manufacturing performance may deteriorate rapidly, thus causing operating unbalance and inefficiency. To tackle this problem at minimum cost, this study proposes a multi-thread constrained two-archive evolutionary algorithm (CTAEA) to enable workstation reconfiguration for multi-stage AEFS considering performance deterioration. First, a workstation reconfiguration model that selects the extra cost and alteration of cycle time as the objectives is developed to evaluate the reconfiguration scheme for the multi-stage AEFS. Then, a multi-thread CTAEA is designed to efficiently optimize the established mathematical model that involves a large number of variables making it hard to obtain globally optimal solutions. Finally, a case study is implemented to verify the feasibility and superiority of the proposed method via experimental validation and comparison, respectively.