Scheduling optimization of underground mine trackless transportation based on improved estimation of distribution algorithm
The trend in underground mine development is trackless transportation, and the scheduling optimization of underground mine trackless transportation is a current research hotspot. This paper proposes a truck scheduling optimization method for underground mine trackless transportation based on an impr...
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| Published in: | Expert systems with applications Vol. 245; p. 123025 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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01.07.2024
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | The trend in underground mine development is trackless transportation, and the scheduling optimization of underground mine trackless transportation is a current research hotspot. This paper proposes a truck scheduling optimization method for underground mine trackless transportation based on an improved estimation of distribution algorithm to address the truck scheduling problem in the underground mine trackless transportation process. The transportation process of transport trucks in underground mines is analyzed. The dispatching model of transport trucks in underground mines is constructed based on the requirements of reducing transportation costs and increasing transportation efficiencies, taking into account the truck meeting situation in the ramp section and minimizing the total shift transportation distance and the total waiting time of transport trucks as the objective functions. The improved estimation of distribution algorithm is used to solve the truck scheduling model, resulting in the optimal ore blending and scheduling schemes. The comparative analysis employs a genetic algorithm, particle swarm optimization algorithm, and immune algorithm. The results demonstrate that, compared to other algorithms, the improved estimation of distribution algorithm proposed in this paper has superior performance in terms of convergence speed and the search for the optimal solution. The total number of transportation tasks associated with the optimal ore allocation scheme is at least 82, and the waiting time associated with the optimal scheduling scheme is reduced to 7.5 min. The operation time chart of transport trucks calculated by the optimal dispatching scheme can clearly depict the location of each transport truck at any time during a shift's working time, which has significant guiding significance for the actual truck transportation in the mine. |
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| AbstractList | The trend in underground mine development is trackless transportation, and the scheduling optimization of underground mine trackless transportation is a current research hotspot. This paper proposes a truck scheduling optimization method for underground mine trackless transportation based on an improved estimation of distribution algorithm to address the truck scheduling problem in the underground mine trackless transportation process. The transportation process of transport trucks in underground mines is analyzed. The dispatching model of transport trucks in underground mines is constructed based on the requirements of reducing transportation costs and increasing transportation efficiencies, taking into account the truck meeting situation in the ramp section and minimizing the total shift transportation distance and the total waiting time of transport trucks as the objective functions. The improved estimation of distribution algorithm is used to solve the truck scheduling model, resulting in the optimal ore blending and scheduling schemes. The comparative analysis employs a genetic algorithm, particle swarm optimization algorithm, and immune algorithm. The results demonstrate that, compared to other algorithms, the improved estimation of distribution algorithm proposed in this paper has superior performance in terms of convergence speed and the search for the optimal solution. The total number of transportation tasks associated with the optimal ore allocation scheme is at least 82, and the waiting time associated with the optimal scheduling scheme is reduced to 7.5 min. The operation time chart of transport trucks calculated by the optimal dispatching scheme can clearly depict the location of each transport truck at any time during a shift's working time, which has significant guiding significance for the actual truck transportation in the mine. |
| ArticleNumber | 123025 |
| Author | Jia, Mingtao Li, Ning Wang, Qizhou Ye, Haiwang Wu, Yahui Wang, Liguan |
| Author_xml | – sequence: 1 givenname: Ning orcidid: 0000-0001-8855-9527 surname: Li fullname: Li, Ning email: 13875910191@163.com organization: Hubei Key Laboratory of Mineral Resources Processing and Environment, Wuhan University of Technology, Wuhan, Hubei 430070, China – sequence: 2 givenname: Yahui surname: Wu fullname: Wu, Yahui organization: School of Resource and Environment Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China – sequence: 3 givenname: Haiwang surname: Ye fullname: Ye, Haiwang email: yehaiwang@sina.com organization: Hubei Key Laboratory of Mineral Resources Processing and Environment, Wuhan University of Technology, Wuhan, Hubei 430070, China – sequence: 4 givenname: Liguan surname: Wang fullname: Wang, Liguan organization: School of Resource and Safety Engineering, Central South University, Changsha, Hunan 410083, China – sequence: 5 givenname: Qizhou surname: Wang fullname: Wang, Qizhou email: wqz@whut.edu.cn organization: Hubei Key Laboratory of Mineral Resources Processing and Environment, Wuhan University of Technology, Wuhan, Hubei 430070, China – sequence: 6 givenname: Mingtao surname: Jia fullname: Jia, Mingtao organization: School of Resource and Safety Engineering, Central South University, Changsha, Hunan 410083, China |
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| Keywords | Underground mine Trackless transportation Ore blending scheme Estimation of distribution algorithm Scheduling optimization |
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