This study proposes a method for autonomously generating paths for multiple autonomous agents to consecutively form a sequence of patterns. Consecutive pattern formation using multiple agents has been used in several applications. Although sophisticated processes such as collision-free path generation are required to operate longer, conventional studies have only focused on minimizing the total distance traveled by all agents to reduce the overall battery consumption. This causes unbalanced loads among agents, leading to battery shortages in a few agents and forcing them to withdraw from the collective work. Our method for consecutive pattern formation is based on ant colony optimization, balancing between fairness in travel distances and minimization of the total distance. Thereafter, we incorporate another method based on particle swarm optimization into our method to automatically determine the parameter values required to control the balance. Experiments demonstrate that the proposed method can perform more formations with the same battery capacity as the baseline method.