Addressing the resource constraints, such as manpower and equipment, faced by mine backfilling operations, this study proposed an optimization model for backfill scheduling based on the Resource-Constrained Project Scheduling Problem (RCPSP). The model considered backfilling’s multi-process, multi-task, and multi-resource characteristics, aiming to minimize total delay time. Constraints included operational limits, resource requirements, and availability. The goal was to determine optimal resource configurations for each stope’s backfilling steps. A heuristic genetic algorithm (GA) was employed for solution. To handle equipment unavailability, a new encoding/decoding algorithm ensured resource availability and continuous operations. Case verification using real mine data highlights the advantages of the model, showing a 20.6% decrease in completion time, an 8 percentage point improvement in resource utilization, and a 47.4% reduction in overall backfilling delay time compared to traditional methods. This work provides a reference for backfilling scheduling in similar mines and promotes intelligent mining practices.

This study systematically investigates the effects of shell ash (SA) content (0–10%) on early moisture evolution, pore structure, and hydration kinetics in cement paste using LF-NMR and NG-I-D hydration kinetic models. Key findings include the following: (1) Increased SA content significantly alters moisture phase distribution. Low contents (≤8%) consume free water through rapid CaO hydration, promoting C-S-H gel densification. However, 10% SA causes reduced moisture in 0.16–0.4 μm gel micropores (due to hindered ion diffusion) and abrupt increases in 0.63–2.5 μm pores. (2) Porosity first decreases then increases with SA content, reaching minimum values at 3–5% and 8%, respectively. The 10% content induces abnormal porosity growth from localized over-densification following polynomial fitting (R² = 0.966). (3) Krstulovic–Dabic model analysis reveals three consecutive hydration stages: nucleation–growth (NG), phase boundary reaction (I), and diffusion control (D). The NG stage shows the most intense reactions, while the D stage dominates (>60% contribution), with high model fitting accuracy (R² > 0.9). (4) SA delays nucleation/crystal growth, inducing needle-like crystals at 3% content. Mechanical properties exhibit quadratic relationships with SA content, achieving peak compressive strength (18.6% increase vs. control) at 5% SA. This research elucidates SA content thresholds governing hydration kinetics and microstructure evolution, providing theoretical support for low-carbon cementitious material design.