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To pursue energy conservation, emission reduction and maximization of net profit, a permutation flow shop order acceptance and scheduling model is formulated. Tabu search is a heuristic global optimization algorithm. Traditional tabu search relies on the initial solution, and it is hard to optimize the permutation flow shop scheduling problem considering energy efficiency. Because of the problem complexity, an energy-saving hybrid tabu search algorithm is proposed, which combines the advantages of the NEH construction heuristic algorithm. Besides, the order acceptance and rejection coding method, energy consumption adjustment and due date assignment policy are designed. Finally, a large number of random examples are used to analyze the performance. Experimental results show that through the above improvements, the algorithm's global search capability and the ability to solve complex models are improved. Comparing with the single algorithm, energy-saving hybrid tabu search has better performance, and it can effectively increase the total net profit and reduce energy consumption.