Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm
To achieve a rational allocation of real-time operational equipment, such as excavators and dump trucks, in open-pit mines, and thereby enhance truck–shovel coordination, this paper addresses the challenges posed by unreasonable on-site scheduling, which includes excessive truck waiting times and pr...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/1/60 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549305781944320 |
|---|---|
| author | Fudong Li Zonghao Shi Weiqiang Ding Yongjun Gan |
| author_facet | Fudong Li Zonghao Shi Weiqiang Ding Yongjun Gan |
| author_sort | Fudong Li |
| collection | DOAJ |
| description | To achieve a rational allocation of real-time operational equipment, such as excavators and dump trucks, in open-pit mines, and thereby enhance truck–shovel coordination, this paper addresses the challenges posed by unreasonable on-site scheduling, which includes excessive truck waiting times and prolonged excavator boom-and-dipper operations. Ultimately, the paper aims to attain optimal truck–shovel coordination efficiency. To this end, we construct a scheduling optimization model, with the production capacities of trucks and shovels serving as constraints. The objective functions of this model focus on minimizing transportation costs, reducing truck waiting times, and shortening excavator boom-and-dipper operation durations. To solve this model, we have developed an improved genetic algorithm that integrates roulette wheel selection and elite preservation strategies. The experimental results of our algorithm demonstrate that it can provide a more refined operational equipment scheduling scheme, effectively decreasing truck transportation costs and enhancing equipment utilization efficiency in open-pit mines. |
| format | Article |
| id | doaj-art-d710dce8393c40bdb6a43b44500d895d |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-d710dce8393c40bdb6a43b44500d895d2025-01-10T13:16:58ZengMDPI AGEnergies1996-10732024-12-011816010.3390/en18010060Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic AlgorithmFudong Li0Zonghao Shi1Weiqiang Ding2Yongjun Gan3School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing 100192, ChinaSchool of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing 100192, ChinaSchool of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing 100192, ChinaTo achieve a rational allocation of real-time operational equipment, such as excavators and dump trucks, in open-pit mines, and thereby enhance truck–shovel coordination, this paper addresses the challenges posed by unreasonable on-site scheduling, which includes excessive truck waiting times and prolonged excavator boom-and-dipper operations. Ultimately, the paper aims to attain optimal truck–shovel coordination efficiency. To this end, we construct a scheduling optimization model, with the production capacities of trucks and shovels serving as constraints. The objective functions of this model focus on minimizing transportation costs, reducing truck waiting times, and shortening excavator boom-and-dipper operation durations. To solve this model, we have developed an improved genetic algorithm that integrates roulette wheel selection and elite preservation strategies. The experimental results of our algorithm demonstrate that it can provide a more refined operational equipment scheduling scheme, effectively decreasing truck transportation costs and enhancing equipment utilization efficiency in open-pit mines.https://www.mdpi.com/1996-1073/18/1/60open-pit minetransportation coststruck waiting timesexcavator boom-and-dipper operation durationsimproved genetic algorithm |
| spellingShingle | Fudong Li Zonghao Shi Weiqiang Ding Yongjun Gan Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm Energies open-pit mine transportation costs truck waiting times excavator boom-and-dipper operation durations improved genetic algorithm |
| title | Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm |
| title_full | Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm |
| title_fullStr | Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm |
| title_full_unstemmed | Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm |
| title_short | Intelligent Optimization Scheduling Strategy for Energy Consumption Reduction for Equipment in Open-Pit Mines Based on Enhanced Genetic Algorithm |
| title_sort | intelligent optimization scheduling strategy for energy consumption reduction for equipment in open pit mines based on enhanced genetic algorithm |
| topic | open-pit mine transportation costs truck waiting times excavator boom-and-dipper operation durations improved genetic algorithm |
| url | https://www.mdpi.com/1996-1073/18/1/60 |
| work_keys_str_mv | AT fudongli intelligentoptimizationschedulingstrategyforenergyconsumptionreductionforequipmentinopenpitminesbasedonenhancedgeneticalgorithm AT zonghaoshi intelligentoptimizationschedulingstrategyforenergyconsumptionreductionforequipmentinopenpitminesbasedonenhancedgeneticalgorithm AT weiqiangding intelligentoptimizationschedulingstrategyforenergyconsumptionreductionforequipmentinopenpitminesbasedonenhancedgeneticalgorithm AT yongjungan intelligentoptimizationschedulingstrategyforenergyconsumptionreductionforequipmentinopenpitminesbasedonenhancedgeneticalgorithm |