Abstract: This study, pertinent to the problem that the traditional process optimization of assembly line optimizes only for single target but neglects other important elements, builds the mathematical model for the multi-objective, including maximizing the capacity, balancing the load and minimizing the cost, process optimization of the assembly line of the passenger car engine. Based on the features of the passenger car engine assembly, such as complex steps, too many stations, expensive tools and great market demands, this paper adopts the GASA algorithm combining the genetic algorithm and the simulated annealing algorithm for solution. Experiments show that such model and algorithm can solve the process optimization problems of the passenger car engine assembly line effectively.