地下煤矿采矿设备协调调度优化策略

Tianyan Liu, Biao Wang, Hanzhao Liu, Bicheng Tang, Ji Ke, Changqing Wang, Aijun Li, Zhigang Ren
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引用次数: 0

摘要

针对射孔采矿中井下采矿设备的调度问题,本文提出了一种改进的文化基因算法(MA)。全局搜索采用遗传算法,并对其交叉和变异操作进行了一些调整;局部搜索采用模拟退火算法。全局搜索采用遗传算法,并在其交叉和变异操作中做了一些调整;局部搜索采用模拟退火算法,考虑到算法会有一定概率跳出最优解范围,因此在原算法的基础上,将高斯函数改为考奇函数,以避免这一问题。将该算法应用于 5S15J 场景进行仿真实验。实验结果表明,改进后的 MA 算法在总时间和总间隔时间上明显优于遗传算法,能得到高质量的解,是一种理想的协同调度策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coordinated scheduling optimisation strategy of mining equipment in underground coal mines
Aiming at the scheduling problem of underground mining equipment in shot mining, this paper proposes an improved cultural gene algorithm (MA). The global search applies the genetic algorithm, and some adjustments are made in its crossover and mutation operations; the local search uses the simulated annealing algorithm. The global search applies the genetic algorithm, and some adjustments are made in its crossover and mutation operations; the local search uses the simulated annealing algorithm, considering that the algorithm will have a certain probability to jump out of the optimal solution range, so on the basis of the original algorithm, the Gaussian function is replaced by the Cauchy function to avoid this problem. The algorithm is applied to the scenario of 5S15J for simulation experiments. After that, compared with the results of the genetic algorithm, it shows that the improved MA algorithm is obviously better in total time and total interval time, and can obtain high-quality solutions and an ideal cooperative scheduling strategy.
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