@inproceedings{e694e1b012a9430588a7e043837d0087,
title = "Coordinated scheduling optimisation strategy of mining equipment in underground coal mines",
abstract = "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.",
keywords = "cultural genes, genetic algorithms, mining, mining equipment, scheduling",
author = "Tianyan Liu and Biao Wang and Hanzhao Liu and Bicheng Tang and Ji Ke and Changqing Wang and Aijun Li and Zhigang Ren",
note = "Publisher Copyright: {\textcopyright} 2024 SPIE.; 3rd International Conference on Algorithms, Microchips, and Network Applications, AMNA 2024 ; Conference date: 08-03-2024 Through 10-03-2024",
year = "2024",
doi = "10.1117/12.3032028",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Joan Lu and Reggie Davidrajuh",
booktitle = "Third International Conference on Algorithms, Microchips, and Network Applications, AMNA 2024",
}