This study explores how to balance cooperation and competition among multiple players in synchro-modal transportation systems. Synchro-modality integrates various transport modes (e.g., rail, ship, and truck) to improve logistics efficiency, but its implementation is challenged by competition among independent stakeholders. To address this issue, the research proposes a multi-objective optimization framework that functions as a central coordination mechanism. The model simultaneously considers transportation cost, environmental impact, and operational constraints while capturing the interactions among heterogeneous players. Numerical experiments demonstrate that system wide optimization significantly outperforms decentralized decision making in terms of overall efficiency. In particular, under limited capacity and homogeneous player preferences, competition intensifies and leads to inefficient outcomes, whereas coordinated optimization effectively reallocates resources and reduces conflicts. The results also reveal a trade-off between efficiency and robustness, suggesting that coordination mechanisms should be designed according to operational conditions. Overall, this study provides a quantitative foundation for improving cooperation in open logistics networks and offers practical insights for designing efficient and sustainable transport systems.

The result of this study was presented in 11th International Physical Internet Conference(IPIC 2025).