Abstract: Objectives To address the cooperative control problem of multi-tug towing systems characterized by multiple constraints and strong physical coupling, a multi-objective particle swarm optimization (MOPSO) method integrated with a multi-criterion switching strategy is proposed. Methods A dynamic model of the multi-tug towing system is first established and transformed into a multi-objective optimization problem. Then, a velocity and position update mechanism for the particle swarm is designed to construct a MOPSO-based control framework. On this basis, a multi-criterion switching strategy is introduced to enhance the system’s adaptability across different operating scenarios and improve the global optimality of the solution. Results Simulation results demonstrate that, compared with the traditional optimal control method, the proposed approach improves the convergence speed by 21.88%, while reducing the towed ship’s longitudinal and lateral errors by 43.39% and 48.99%, respectively. The tracking errors of all four tugs are also reduced, resulting in smoother and more compact formation control. Furthermore, compared with the single-criterion method, the proposed multi-criterion switching strategy achieves a more uniform Pareto front distribution, with the solution set closer to the ideal optimal region. The convergence speed is improved by 7.41%, and the longitudinal and lateral errors of the towed ship are reduced by 11.47% and 10.27%, respectively, achieving a better balance among multiple objectives. Conclusions The proposed method enhances the control accuracy of the towed ship while achieving coordinated control among tugs and optimal balance of overall system performance.