Doing Risky works continuously by an operator can result in harmful effects on the health and performance of operator over time because of ergonomic hazards. In order to reduce these negative effects, it is necessary for the labors to be exposed to such dangers with the same amount. A branch of operation research that analyzes the allocation of staff to different tasks in order to balance the ergonomic risks and complications of doing continuous risky works in planning horizon in known as job rotation.In the present work, we want to simulate the job rotation problem of staff with different skills in cell production systems and show the efficiency of meta-heuristic algorithms to solve this NP_Hard model. In order to evaluate the efficiency of the proposed solutions, a number of sample problems have been generated randomly and they have been solved by meta-heuristic simulated annealing, and then its results has been compared with accurate methods of optimization in which the comparison of these results shows the high efficiency of proposed meta-heuristic algorithm and the better performance in the quality of results considering time resolution.