The arc welding robot can improve the production efficiency in the actual production process． The path length and energy consumption during the welding process were optimized，and an adaptive neighborhood discrete multi-objective optimization algorithm based on event triggering (DMOEA/D-ET) was proposed． The algorithm uses the updated particle ratio as the event trigger mechanism to coordinate the global search and the local search through the event trigger mechanism． The grid method was used for global search and MOEA/D for local search． The problem of uneven distribution of MOEA/D algorithm was improved by adopting adaptive neighborhood stra- tegy． By comparing with the other five algorithms on three TSPLIB problems，the experimental results show that the proposed algorithm has better performance． Finally，multi-objective optimization was carried out for the wel- ding process of the balanced beam model． Compared with the other five multi-objective algorithms，the results show that the proposed algorithm is closer to the real frontier and has better distribution of the solution．