Batch processing machines can process several job simultaneously and are encountered in many manufacturing environments. Jobs in a batch are processed together and have the same start and end processing time. Since jobs are non-identical in job sizes and job processing times, they should be reasonably scheduled to improve the machine utilisation and processing efficiency. Two well-known heuristics, first fit longest processing time and best fit longest processing time (BFLPT), are improved in this study by considering identical job sizes and then BFLPT is further improved by an enumeration scheme proposed. Computational experiments are conducted to evaluate the performance of the improvement and the results are compared with the existing heuristics.

Under the background of the intelligent construction of a coal mine, how to efficiently extract effective information from the massive monitoring data of mine earthquakes, and improve prediction accuracy, is a research hotspot in the field of coal mine safety production. In view of this problem, more and more machine learning methods are being applied to the prediction on mine earthquakes. Considering that clustering analysis can enhance the correlation between microseism data, we propose a method whose main idea is to cluster microseism data before establishing the prediction model, and then train the model, so as to improve prediction accuracy. Specifically, microseism events on a working face are divided into clusters in advance by the Spatial Temporal-DBSCAN(ST-DBSCAN) algorithm, then a prediction model is established with Support Vector Regression (SVR) to predict the occurrence location and daily frequency of high-energy mine earthquake events. A set of engineering experiments were conducted in H Coal Mine, and the results show that the spatial-temporal clustering analysis of microseism events can indeed improve the prediction accuracy of machine learning methods on mine earthquakes.

The problem of minimizing the makespan on single batch processing machine is studied in this paper. Both job sizes and processing time are nonidentical and the processing time of each batch is determined by the job with the longest processing time in the batch. Max–Min Ant System (MMAS) algorithm is developed to solve the problem. A local search method MJE (Multiple Jobs Exchange) is proposed to improve the performance of the algorithm by adjusting jobs between batches. Preliminary experiment is conducted to determine the parameters of MMAS. The performance of the proposed MMAS algorithm is compared with CPLEX as well as several other algorithms including ant cycle (AC) algorithm, genetic algorithm (GA), and two heuristics, First Fit Longest Processing Time (FFLPT) and Best Fit Longest Processing Time (BFLPT), through numerical experiment. The experiment results show that MMAS outperformed others especially for large population size.

With the depletion of shallow coal resources, deep extra-thick coal seam mining has become vital for energy security, yet fully mechanized top-coal caving (FMTC) goaf-side roadways face severe challenges of excessive advanced deformation and intense strata behavior. To address this gap, this study took the 4301 tailgate of a coal mine in Shaanxi province as the engineering background, integrating field investigation, theoretical analysis, FLAC^3D numerical simulation, and industrial tests. Guided by the key stratum theory, we systematically analyzed the influence of overlying key strata fracture on strata pressure. The results show three key strata: near-field secondary key strata (KS1, KS2) with “vertical O-X” fracturing and far-field main key stratum (MKS) with “horizontal O-X” fracturing. The radial extrusion force from MKS rotational blocks is the core cause of 200 m range advanced deformation. A collaborative control scheme of near-field key strata directional fracturing roof-cutting pressure relief and high-strength bolt-cable support was proposed. Industrial verification indicates roadway deformation was significantly reduced, with roof subsidence, floor heave, and rib convergence controlled within safe engineering limits. This study fills the gap of insufficient research on far-field key strata’s impact, providing a reliable technical solution for similar extra-thick coal seam FMTC goaf-side roadway surrounding rock control.