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This paper propose a genetic algorithm based on extended Giffler & Thompson (EGT) procedure for hybrid flow shop (HFS) scheduling problem. In this method, each individual represents a complete schedule. The crossover and mutation operators are designed based on EGT algorithm. This algorithm is also used to generate initial population. Therefore, the search space is restricted to the active schedule space. Last, the performance of this algorithm is analyzed by computational experiments using benchmark instances. The results suggest that the proposed algorithm can find optimal solutions for all the easy problems, while optimal or near-optimal solutions for relatively hard problems.