Citation: Li, N.; Feng, S.; Lei, T.; Ye,
H.; Wang, Q.; Wang, L.; Jia, M.
Rescheduling Plan Optimization of
Underground Mine Haulage
Equipment Based on Random
Breakdown Simulation. Sustainability
2022, 14, 3448. https://doi.org/
10.3390/su14063448
Academic Editors: João Carlos de
Oliveira Matias, Paolo Renna and
Yoshiki Shimomura
Received: 26 January 2022
Accepted: 14 March 2022
Published: 15 March 2022
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Article
Rescheduling Plan Optimization of Underground Mine
Haulage Equipment Based on Random Breakdown Simulation
Ning Li
1,2,
* , Shuzhao Feng
1,
*, Tao Lei
1,2,
*, Haiwang Ye
1
, Qizhou Wang
1
, Liguan Wang
3
and Mingtao Jia
3
1
School of Resource and Environment Engineering, Wuhan University of Technology, Wuhan 430070, China;
yehaiwang@sina.com (H.Y.); wqz@whut.edu.cn (Q.W.)
2
Hubei Key Laboratory of Mineral Resources Processing and Environment, Wuhan 430070, China
3
School of Resource and Safety Engineering, Central South University, Changsha 410083, China;
13808478410@163.com (L.W.); mingtao_jia@163.com (M.J.)
* Correspondence: 13875910191@163.com (N.L.); fsz2224284697@163.com (S.F.); leitao539@163.com (T.L.);
Tel.: +86-138-7591-0191 (N.L.)
Abstract:
Due to production space and operating environment requirements, mine production equip-
ment often breaks down, seriously affecting the mine’s production schedule. To ensure the smooth
completion of the haulage operation plan under abnormal conditions, a model of the haulage equip-
ment rescheduling plan based on the random simulation of equipment breakdowns is established in
this paper. The model aims to accomplish both the maximum completion rate of the original mining
plan and the minimum fluctuation of the ore grade during the rescheduling period. This model is
optimized by improving the wolf colony algorithm and changing the location update formula of
the individuals in the wolf colony. Then, the optimal model solution can be used to optimize the
rescheduling of the haulage plan by considering equipment breakdowns. The application of the pro-
posed method in an underground mine revealed that the completion rate of the mine’s daily mining
plan reached 83.40% without increasing the amount of equipment, while the ore quality remained
stable. Moreover, the improved optimization algorithm converged quickly and was characterized by
high robustness.
Keywords:
project scheduling; underground mine; random breakdown simulation; wolf colony
algorithm; multi-objective optimization
1. Introduction
To reduce the waste of various resources and indirectly protect the environment, the
proposal of the concept of the green mine requires a scientific mining process and efficient
utilization of equipment resources. Standardized and intensive mining are the main mining
modes of the future. Underground production equipment is gradually developing in a
large-scale and intelligent direction. Therefore, effectively improving the mining efficiency
and equipment utilization will become one of the key parameters for developing green
mines and improving the economic benefits of mining enterprises. With the continuous
development of information technology, big data, and artificial intelligence, intelligent
mining theory and technology have come a long way, thereby providing basic support for
the transformation of mining enterprises from extensive to refined. Optimal preparation
of production plans and reasonable equipment scheduling are important aspects of green
mines and intelligent mining. However, due to factors such as the mining environment,
equipment performance, and personnel quality, abnormal conditions such as equipment
breakdowns and safety accidents will inevitably occur during the production process. As a
result, the original scheduling plan may not be completed, which in turn affects the overall
production schedule of the mine and the economic benefits of the enterprise. Therefore,
solving the problem of production equipment rescheduling under abnormal conditions and
Sustainability 2022, 14, 3448. https://doi.org/10.3390/su14063448 https://www.mdpi.com/journal/sustainability
