Comparative Analysis of the Filling material Cost of a Metal Mine Based on the Optimized Fruit Fly Optimization Algorithm

The cost of different filling materials is analysed to guide metal mine production.Taking Jinchuan nickel mine as the research background, the minimum filling cost constraint optimization problem was established based on the unary nonlinear regression, curve estimation and constraint optimization theories, combined with the 28d strength, collapse and stratification orthogonal test results of limestone powder and fly ash filling material.The mathematical model R² of each constraint condition in the constraint optimization problem was higher than 90%.Finally, the OFOA algorithm and PSO algorithm were used to solve the average minimum filling cost.The calculated results of the OFOA were 91.615yuan/kg and 97.092yuan/kg (the filling cost with limestone powder was 5.477yuan/kg lower than that with fly ash), but the PSO algorithm did not find the optimal filling cost solution.The results show that:(1) Using the theory of unitary nonlinear regression and curve estimation, a high-precision multivariate nonlinear mathematical model can be established according to different constraints;(2) The improved OFOA algorithm can solve the cost constraint optimization problem of different filling materials;(3) Compared with the FOA and PSO, the improved algorithm has a faster convergence rate and a more stable calculation process.The above research methods can be used to carry out cost-comparative analyses on different metal mines, filling materials and constraint conditions, providing theoretical guidance for filling material selection.