This paper explores formation control for multiagent systems by reformulating desired formations using signal temporal logic (STL) specifications. To achieve flexibility and efficiency, we employ sparse polynomial zonotopes (SPZs) to represent several common formations and the system's state sets. This representation allows us to frame the formation control problem as a series of transitions between different state sets within a specific time horizon, which can be solved using optimal transport theory. By combining the optimal transport matrix with shrinking horizon model predictive control (MPC), we have developed a feasible control strategy that gradually guides the system trajectories toward the target set. This innovative approach decomposes the formation control problem into multiple temporal logic subproblems, reducing computational complexity and mitigating the impact of sampling randomness introduced by optimal transport. The effectiveness of our proposed approach is demonstrated through its application to a multi-unicycle system.