Research on the Application of Intelligent Optimization Algorithms in the Field of Mineral Processing
Authors: Zhang Wei, Li Ming, Wang Fang
This paper investigates the application of intelligent optimization algorithms in mineral processing, focusing on the optimization of flotation parameters and grinding circuits. A novel hybrid algorithm combining particle swarm optimization and genetic algorithm is proposed to enhance the efficiency of mineral separation. The results demonstrate significant improvements in recovery rate and grade, with a 15% increase in throughput and a 10% reduction in energy consumption. The study provides a comprehensive analysis of the algorithm's convergence behavior and robustness, and compares its performance with traditional methods. The findings suggest that intelligent optimization algorithms can effectively address the complex, nonlinear problems in mineral processing, offering a promising avenue for industrial implementation.
