A Novel Lifting Point Location Optimization Method of Transmission Line Tower Based on Improved Grey Wolf Optimizer

Abstract

Abstract There are some deficiencies in the Grey Wolf Optimizer (GWO) when optimizing the four-point lifting location of the transmission line tower, such as low optimization efficiency and easy to fall into a local minimum. Therefore, this study proposes an optimization method for the four-point lifting location of transmission line towers based on improved GWO. The good point-set is used to improve the initialization method of gray wolf individuals in order to ensure the uniform distribution of population position and reduce the invalid search in the early stage of optimization. Two random operators are used to adjust the optimal gray wolf position by combination mutation, which enhances the ability of the algorithm to jump out of the local optimum. Finally, the median of gray wolf population is used to consider the trend information of optimization process, and the stability of optimization algorithm is improved. Through the simulation experiment of the improved algorithm and comparison with genetic algorithm, particle swarm optimization algorithm, and artificial fish swarm algorithm. The results show that the improved algorithm has a better effect and faster convergence speed in solving the optimization problem, and it is better than other optimization algorithms in the optimization problem of the four-point lifting of transmission line tower.