Spot welding robot is widely used in industrial field,and reasonable welding sequence can improve production efficiency.In order to achieve the optimal path planning of spot welding robot,a multi-objective problem model for spot welding path and working time was established,and a multi-objective equilibrium optimizer algorithm (DMONEO) combined with improved fast non-dominated sorting was proposed.Adding fast non-dominated sorting and adopting survival scoring strategy instead of crowding factor can better maintain the diversity of the population and prevent premature convergence of DMONEO.TSPLIB benchmark experiment results show that the proposed DMONEO algorithm performs better than other algorithms.Finally,the simulation experiment was carried out in the path planning model of the actual spot welding robot and compared with other algorithms.The results show that the optimization effect of the proposed algorithm is better and the time consumption is shorter.