Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines
In order to solve the problem of low-carbon transportation scheduling in open-pit mines, the mathematical model is established by taking the mining volume, crushing volume of crushing stations and the number of trucks as constraints and taking the minimum sum of carbon emission cost and transportati...
| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Industry and Mine Automation
2020-12-01
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| Series: | Gong-kuang zidonghua |
| Subjects: | |
| Online Access: | http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2020070049 |
| _version_ | 1818720888858607616 |
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| author | MEN Fei JIANG Xi |
| author_facet | MEN Fei JIANG Xi |
| author_sort | MEN Fei |
| collection | DOAJ |
| description | In order to solve the problem of low-carbon transportation scheduling in open-pit mines, the mathematical model is established by taking the mining volume, crushing volume of crushing stations and the number of trucks as constraints and taking the minimum sum of carbon emission cost and transportation cost as the objective function. An improved gray wolf optimization algorithm is proposed for the problem that gray wolf optimization algorithm is easy to fall into local optimum when it is used to solve the low-carbon transportation scheduling problem of open-pit mines. The algorithm introduces migration operation in the gray wolf optimization algorithm and dynamically modifies the migration probability of the gray wolf optimization algorithm according to its fitness function value. It is beneficial to go beyond the local optimum and obtain the global optimum faster so as to effectively balance the global optimization ability and local optimization ability. Experimental results show that the algorithm has higher optimization accuracy and faster optimization speed. By applying this algorithm to optimize low-carbon transportation scheduling in open-pit mines, transportation efficiency has been improved and carbon emissions and transportation costs have been reduced. |
| first_indexed | 2024-12-17T20:30:00Z |
| format | Article |
| id | doaj.art-9b13bb202fdc4346802901f84ce7246a |
| institution | Directory Open Access Journal |
| issn | 1671-251X |
| language | zho |
| last_indexed | 2024-12-17T20:30:00Z |
| publishDate | 2020-12-01 |
| publisher | Editorial Department of Industry and Mine Automation |
| record_format | Article |
| series | Gong-kuang zidonghua |
| spelling | doaj.art-9b13bb202fdc4346802901f84ce7246a2022-12-21T21:33:37ZzhoEditorial Department of Industry and Mine AutomationGong-kuang zidonghua1671-251X2020-12-014612909410.13272/j.issn.1671-251x.2020070049Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit minesMEN FeiJIANG XiIn order to solve the problem of low-carbon transportation scheduling in open-pit mines, the mathematical model is established by taking the mining volume, crushing volume of crushing stations and the number of trucks as constraints and taking the minimum sum of carbon emission cost and transportation cost as the objective function. An improved gray wolf optimization algorithm is proposed for the problem that gray wolf optimization algorithm is easy to fall into local optimum when it is used to solve the low-carbon transportation scheduling problem of open-pit mines. The algorithm introduces migration operation in the gray wolf optimization algorithm and dynamically modifies the migration probability of the gray wolf optimization algorithm according to its fitness function value. It is beneficial to go beyond the local optimum and obtain the global optimum faster so as to effectively balance the global optimization ability and local optimization ability. Experimental results show that the algorithm has higher optimization accuracy and faster optimization speed. By applying this algorithm to optimize low-carbon transportation scheduling in open-pit mines, transportation efficiency has been improved and carbon emissions and transportation costs have been reduced.http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2020070049open-pit mine transportationlow-carbontransportation schedulinggray wolf optimization algorithmmigration operatio |
| spellingShingle | MEN Fei JIANG Xi Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines Gong-kuang zidonghua open-pit mine transportation low-carbon transportation scheduling gray wolf optimization algorithm migration operatio |
| title | Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines |
| title_full | Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines |
| title_fullStr | Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines |
| title_full_unstemmed | Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines |
| title_short | Improved gray wolf optimization algorithm for solving low-carbon transportation scheduling problem in open-pit mines |
| title_sort | improved gray wolf optimization algorithm for solving low carbon transportation scheduling problem in open pit mines |
| topic | open-pit mine transportation low-carbon transportation scheduling gray wolf optimization algorithm migration operatio |
| url | http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2020070049 |
| work_keys_str_mv | AT menfei improvedgraywolfoptimizationalgorithmforsolvinglowcarbontransportationschedulingprobleminopenpitmines AT jiangxi improvedgraywolfoptimizationalgorithmforsolvinglowcarbontransportationschedulingprobleminopenpitmines |