In the green backfilling mining of underground coal mines, gangue in a coal seam is used to replace and fill goafs. However, the gas drainage time changes in the amount of gangue output and order in the extraction sequence of stope blocks, thereby changing the production output. A multi-objective integer programming model was proposed to solve this based on an improved non-dominated sorting genetic algorithm. The results show a feasible gangue filling rate can be found and the extraction sequence for a long-term planning time is optimized. It increases the planned annual output by 26% and reduces equipment idle time.

中文翻译：

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基于NSGA-II的地下充填开采优化生产调度

在地下煤矿绿色充填开采中，利用煤层中的矸石代替和填充采空区。但瓦斯抽采时间会随着采场区块开采顺序中脉石产量和顺序的变化而变化，从而改变产量。针对这一问题，提出了一种基于改进的非支配排序遗传算法的多目标整数规划模型。结果表明，可以找到可行的矸石充填率，并优化了长期规划时间的提取顺序。使计划年产量提高26%，减少设备闲置时间。