Coordinated scheduling optimisation strategy of mining equipment in underground coal mines

Tianyan Liu, Biao Wang, Hanzhao Liu, Bicheng Tang, Ji Ke, Changqing Wang, Aijun Li, Zhigang Ren

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名Third International Conference on Algorithms, Microchips, and Network Applications, AMNA 2024
编辑Joan Lu, Reggie Davidrajuh
出版商SPIE
ISBN(电子版)9781510680098
DOI
出版状态已出版 - 2024
活动3rd International Conference on Algorithms, Microchips, and Network Applications, AMNA 2024 - Jinan, 中国
期限: 8 3月 202410 3月 2024

出版系列

姓名Proceedings of SPIE - The International Society for Optical Engineering
13171
ISSN(印刷版)0277-786X
ISSN(电子版)1996-756X

会议

会议3rd International Conference on Algorithms, Microchips, and Network Applications, AMNA 2024
国家/地区中国
Jinan
时期8/03/2410/03/24

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