Combining the advantage of a distributional fragment vocabulary and the sequential translation scheme, we propose Fragment-based Sequential Tanslation (FaST), which is realized by an RL policy that proposes fragment addition/deletion to a given molecule. Our proposed method unifies molecular optimization and translation and can generate molecules under various objectives such as property constraints, novelty constraints, and diversity constraints. The main contribution of this paper includes: