Underground mining is a complex dynamic system. Traditional static analytical methods are insufficient to characterize the operational behavior and efficiency variations in such systems under coupled multidimensional constraints. To address this limitation, this study proposes a novel hybrid simulation-modeling method for underground mining processes with multidimensional constraints. The method integrates discrete-event simulation and agent-based simulation. It reconstructs the spatiotemporal constraints of multiple stopes, process constraints, and organizational constraints into an explicit multidimensional constraint system. Using the upward horizontal layered cut-and-fill mining method at the Sanshandao Gold Mine as an engineering case, a simulation model was established for development, cutting, stoping cycles, haulage, and backfilling. Key factors, including stope availability, backfill curing delays, centralized blasting, shift organization, and equipment availability, were embedded as explicit mechanisms. The results show that simulated operating time, production, and efficiency are generally consistent with field statistical data at multiple scales, including cycle operations, individual stopes, individual horizontal layers, and complete mining blocks. This indicates that the model can effectively reproduce the operating characteristics of the underground mining system under multidimensional constraints. Further analysis shows that production rhythm is governed by the combined effects of stope spatiotemporal relationships, process coordination, backfill waiting, and organizational resource constraints, rather than by single-process capacity. Spatiotemporal and process constraints define operation initiation and advancement sequence, while organizational constraints mainly appear as waiting accumulation, process disturbances, and resource-utilization fluctuations. The proposed method provides a reusable tool for capacity evaluation, production organization analysis, and decision optimization in complex underground mines.
Zou et al. (Fri,) studied this question.