Flexible job-shop scheduling is one of the most critical production management topics. In this paper, it is also assumed job interruption due to the machine breakdown is allowed, and the processing time depends on the speed of the machines and requires both human and machine resources to process the jobs. Although, as the speed of the machine increases, the time of job’ completion reduces, an increase in speed results in an increase in noise pollution in the production environment, and with the aim of applying a cleaner production that is a preventative approach, it has been tried to reduce noise pollution by minimizing the increase in speed. After modeling the problem using the mixed -integer programming and solving it using the ε-constraint method, since the problem is NP-hard, a multi-subpopulation evolutionary algorithm is proposed to solve it. The results showed that considering the Mean Ideal Distance (MID) criterion, the ε-constraint method has a better performance than the proposed algorithm but considering other criteria the proposed algorithm has is better. Also, the proposed algorithm was compared with the NSGA-II in large-size instances and the computational results showed that the proposed algorithm performs better than the NSGA-II in most cases.
