This paper proposes a multi-objective optimization method based on multiple group cooperative adaptive differential evolution algorithm (MCADE) for cable laying problems in power transmission engineering. A threeobjective mathematical model containing the weight of the cable network, the percentage of the main road in the bundling section and the openness of the path is constructed, and the differential evolution algorithm is selected for path optimization. Adaptive multiple swarm strategy and multi-operator parallel search strategy are designed, and the improved MCADE algorithm is proposed. The MCADE algorithm simulates the actual situation of power pipeline network to establish the power laying network, and the MCADE algorithm performs the best among the three algorithms in solving the shortest paths of the two devices, which saves 16.88ms and 12.13ms compared with the ACA and ABC algorithms, respectively, and the average length of the paths in eight power cable laying tasks is only 45.13m, which reduces 45.37m and 68m, respectively, compared with the two traditional path planning methods for laying power cables. Compared with the two traditional power cable laying path planning methods, the average path length is only 45.13m, which reduces 45.37m and 68.78m respectively. The results confirm that the MCADE algorithm can effectively solve the multi-objective conflict problem in complex cable laying scenarios, which provides theoretical support and methodological reference for intelligent design of power projects.