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Genetic algorithm (GA) is a meta-heuristic algorithm with strong global search ability, which can obtain the optimal or near-optimal solution by continuously evolving population; however, the local search ability of GA is poor, so it is easy to occur the problem of premature convergence. Therefore, in order to overcome the problem of premature convergence of GA, considering the advantage of local search ability of tabu search (TS) algorithm, a hybrid algorithm of genetic and tabu search (GA_TS) is proposed to solve the problem of earliness and tardiness penalty in precast production flow shop. The hybrid algorithm is to improve the best chromosomes in the current population by TS after each iteration of the GA, and replace the chromosome with the worst fitness value in the population. The experimental results show that the proposed GA_TS algorithm has better performance and can obtain global optimal solution or near-optimal solution.