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Recently, the manufacturing sector produces the primary source of carbon emissions. Therefore, it must consider the environmental aspect and economic impacts. Carbon emissions have become one of some an essential indicator of the company-s. One of some way to minimize carbon emission is scheduling appropriately. This study aims to reduce carbon emission in the permutation flow shop scheduling problem (PFSP). This problem considers the sequence of dependent set up and removal. We developed the Hybrid Binary Dragonfly Algorithm (HBDA) to solve that issue. In the HBDA, we offered 10% search agent use NEH algorithm. NEH is one of the useful heuristic algorithms. In this study, we did some numerical experiments. It did explore the best algorithm parameter and algorithm effectiveness. Some popular algorithm compares algorithm HBDA. The results show, there is some scenario to decrease carbon emissions in several various problems. Moreover, The HBDA proved useful to reduce carbon emission compared to other algorithms.