In most of the production systems, lot-sizing and scheduling decisions are made at different levels of hierarchy; although there is a strong interaction between these decisions. Furthermore, most of the existing models do not utilize the shop floor conditions in lot-sizing and scheduling decisions, even though such a decision might improve the system performance. In this study, a dynamic lot-sizing and scheduling algorithm is suggested for cellular manufacturing systems, which utilizes a hybrid simulation/analytic modeling approach. The performance of the proposed algorithm is tested against the push and pull systems under different shop floor conditions, and shown that we can improve tardiness, flow time and makespan criteria when comparedto other systems.