针对地下矿山空间受限、设备资源有限以及生产任务重的特点，从相邻工序时间间隔最短及生产总时间最短的角度，构建了预控顶中深孔分段空场嗣后充填采矿法的生产计划优化模型，并采用启发式算法加速的遗传算法求解该模型。以赞比亚某铜矿的实际数据为例，对启发式遗传算法和普通遗传算法求出的染色体适应度进行比较分析。结果表明：相比普通遗传算法启发式遗传算法的求解收敛速度更快，经优化后矿山设备平均利用率为64.8%，平均出矿量为3 631.19 t/d，既能满足开采需求，又能有效缩短作业时间间隔，保证作业安全要求。该算法能够快速有效地解决井下多设备协调问题。

With the rapid development of digital economy in the world，how to realize the rapid optimal allocation of underground mine production equipment has become the key to the continuous advancement and in-depth application of digital mine.In view of the characteristics of underground mines such as limited space，limited equipment resources，and large production tasks，an optimization model was constructed for production planning of the follow-up filling mining method in the open pit using pre-controlled roof medium-and deep-hole and sublevel open-stopping and subsequent filling method.The model aims at minimizing the interval time between adjacent processes and the total production time，and the above issue is solved using genetic algorithms.The genetic algorithms used for solving the problem include traditional genetic algorithms and optimized genetic algorithms.Taking the actual data of a copper mine test stope in Zambia as an example，it can be seen from the iterative results that all genetic algorithms can solve the model，and the optimized genetic algorithm converges faster than the ordinary genetic algorithm.The genetic algorithm accelerated by heuristic algorithm has the fastest convergence speed.Therefore，the heuristic genetic algorithm is used to solve the multi-objective optimization model and the results are visualized.After analyzing the solution results，it is found that the average utilization rate of equipment is only 49.16%，and the utilization rate of some equipment is low，so the number of equipment is optimized.After the number of equipment was optimized and solved again，the average utilization rate of mine equipment increased to 64.8%，basically meeting the requirements of the mine.In terms of production，the daily average ore output is 3 631.19 t/d，which meets the mining demand and effectively shorts the operation time interval to ensure the requirements of mining safety.In addition，copper and cobalt sunrise ore grade fluctuation is small，easy to concentrate.Therefore，the algorithm and model can quickly and effectively solve the problem of multi-equipment coordination in a copper mine in Zambia，improve production efficiency and safe mining.

http://www.goldsci.ac.cn/article/2023/1005-2518/1005-2518-2023-31-4-669.shtml