Abstract
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.
Highlights
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Solving the change of production scheduling caused by "under three", gas drainage, etc.
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Establishing a method to find suitable gangue filling rate in backfilling mining.
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Improving the mixed population coding in the NGSA-II for solving production scheduling.
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Adding an upper layer with greedy strategy to control the Pareto equilibrium frontier.
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Establishing a constraint to limit deadlocks in production scheduling solutions.
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Acknowledgements
This work was supported by the Project of the National Natural Science Foundation of China (no. 51204185, 51974295) and the State Key Development Program for Basic Research of Xuzhou City (No. KC17073).
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Bao, Y., Wang, Y., Zhao, L. et al. Optimization Production Scheduling of Underground Backfilling Mining Based on NSGA-II. Mining, Metallurgy & Exploration 39, 1521–1536 (2022). https://doi.org/10.1007/s42461-022-00606-z
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DOI: https://doi.org/10.1007/s42461-022-00606-z