Application of an Improved Grey Wolf Optimization Algorithm in the Process of Aluminum Electrolysis

In the process of aluminum electrolysis, in order to reduce energy consumption, it is necessary to reasonably configure related operating parameters. In this paper, an improved grey wolf optimization algorithm based on Fuch mapping (FGWO) is proposed to optimize the parameters of aluminum electrolysis. First, chaos initialization, establishment of a new individual position update equation and introduction of Gaussian variation are adopted to reduce the premature convergence probability of the algorithm and improve the ability to jump out of the local optimal solution, and further enhancements to the optimization performance of the algorithm. Second, to compare the effects of different improvement strategies on the performance of the GWO algorithm, the effectiveness of the strategy proposed in this paper is demonstrated. The comparison experiment between the FGWO algorithm and other algorithms proves its advancement. Finally, the Grey Wolf optimization algorithm is applied to a practical optimization problem in the aluminum electrolysis process. The results show that this algorithm not only has good optimization performance and fast convergence speed, but also can effectively solve the actual optimization problem of aluminum electrolysis. Therefore, FGWO algorithm has high practical value.