In this study, we consider the general lot sizing and scheduling problem in flexible flow shop (GLSP-FFS). The GLSP-FFS has not been considered in literature. The GLSP-FFS deals with the issue of determining the lot sizes of several products and simultaneously scheduling them on serially arranged manufacturing stages with parallel machines in each stage to satisfy deterministic and dynamic demand over a finite planning horizon. Each item can be processed on each machine with different process rates and sequence dependent setup times and setup costs. The objective is to minimize all relevant costs, which are inventory, shortage and setup costs. In this study, three mathematical models are designed for this problem and efficiency of these models is discussed. Also a simulated annealing and an efficient hybrid heuristic algorithm consists of integrating simulated annealing and Lagrangean relaxation is proposed. Finally computational results demonstrate the effictiveness of these algorithms in comparison with GAMS software solutions.