Optimization of stope dimensions using response surface method coupling a hybrid chaos-genetic algorithm

To efficiently realize backfilling mining with medium-deep hole caving in a gold mine, the rational determination of stope dimensions is essential. The Vlazov plate theory was employed to analyze the stress state and investigate the relationship between roof thickness and maximum tensile stress under varying stope spans. Since the latter serves as a criterion for evaluating roof strength failure, it is imperative to establish the appropriate range of parameters that ensure the rock mechanics stability during mining operations. Through central composite testing, numerical simulations were conducted to obtain mechanical response characteristics under different stope dimensions. Simultaneously, roof stress distributions and stope stability were analyzed. A second-order response surface model was constructed based on these findings, enabling the formulation of a comprehensive optimization framework. The interaction between variables within this framework was carefully considered when defining the objective functions for optimization. By integrating chaotic mapping into genetic algorithms, a multi-objective optimization approach was implemented, yielding 17 Pareto-optimal solutions. Ultimately, the optimized stope geometry was determined to have a chamber span of 31.89 m, a pillar span of 29.14 m, and a roof thickness of 5.35 m. This configuration represents the optimal balance between mechanical performance and mining efficiency in the context of medium-deep hole caving operations within the gold mine.