Optimization of Aluminum Electrolytic Process Parameters Based on Parallel Tumbleweed Algorithm
Huang Minke · 2023
In order to enhance the optimization capability of process parameters in aluminum electrolysis production, this paper proposes a Parallel Tumbleweed Algorithm (PTA) based on parallel computing. The Tumbleweed Algorithm(TA) is prone to local convergence during the iteration process. The PTA algorithm achieves parallel processing between populations through two communication strategies. First, the optimal values are exchanged between two subpopulations. Second, in a three-subpopulation scenario, a portion of individuals in one subpopulation is replaced with the best individuals from the other two subpopulations. These two types of exchanges allow for the transfer and sharing of the optimal values among the subpopulations. Applying PTA to solve the CEC2017 test functions and comparing it with various intelligent optimization algorithms. The results show that this algorithm has better optimization performance and competitiveness. Finally, applying the PTA algorithm to the aluminum electrolysis parameter optimization problem validates the practicality of the algorithm.