A novel lifting point location optimization method of transmission line tower based on improved grey wolf optimizer

In the erection process of transmission line tower, the appropriate lifting point position is an important factor in ensuring the stability and balance of the lifting process and preventing deformation and damage to the towers. In this paper, a improved grey wolf optimization algorithm is proposed to solve the issues of low optimization efficiency and easily getting trapped in local minima when optimizing the lifting point position of transmission line towers. The improved algorithm includes the use of a good point-set strategy to enhance the initialization method of grey wolf individuals, ensuring a more uniform distribution of the population and reducing ineffective searches in the early stages of optimization. Furthermore, two random operators are utilized to combine and mutate the optimal grey wolf position, thereby enhancing the algorithm's ability to escape local optima. Finally, the trend information of the optimization process is considered, and the median value of the population is used to improve the stability of the optimization algorithm. Experimental results demonstrate that the proposed algorithm has better optimization performance and faster convergence speed compared to genetic algorithm, particle swarm optimization algorithm, and artificial fish swarm algorithm. It effectively addresses the optimization problem of lifting point position for transmission line towers.