Assembly line balancing (ALB) is the problem of assigning a set of tasks to workstations, such that the precedence relations among the tasks are satisfied to optimize different objectives. ALB is an important task for the garment industry. When the product model is changed, the assembly line must be balanced again. There are huge investigations on ALB including different objectives such as minimizing the number of workstations, minimizing the balance delay and minimizing the cycle time. In this paper, the objective of ALB is to minimize the number of workstations for a given cycle time with respect to some constraints on the order of precedence relations among tasks, on the number of tasks and machine types in each group of tasks. We first use the greedy strategy to find an initial solution, then apply the Simulated Annealing (SA) to find the best solutions possible. The proposed algorithms have been evaluated on the actual data set of Dong Van Garment Factory, Hanoi Textile Garment Joint Stock Corporation, Vietnam. The experimentation shows the feasibility to the real -life situation with very fast running time. Especially, we achieved the optimal results on small-size test cases.