Design of an Intelligent Shop Scheduling System Based on Internet of Things
In order to optimize the functionality of automated guidance vehicles (AGVs) in logistics workshops, a wireless charging and task-based logistics intelligent dispatch system was developed based on the Internet of Things. This system aimed to improve freight efficiency in the workshop’s logistics sys...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/17/6310 |
| _version_ | 1797582586668646400 |
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| author | Maoyun Zhang Yuheng Jiang Chuan Wan Chen Tang Boyan Chen Huizhuang Xi |
| author_facet | Maoyun Zhang Yuheng Jiang Chuan Wan Chen Tang Boyan Chen Huizhuang Xi |
| author_sort | Maoyun Zhang |
| collection | DOAJ |
| description | In order to optimize the functionality of automated guidance vehicles (AGVs) in logistics workshops, a wireless charging and task-based logistics intelligent dispatch system was developed based on the Internet of Things. This system aimed to improve freight efficiency in the workshop’s logistics system. The scheduling system successfully addressed the round-trip scheduling issue between AGVs and multiple tasks through two degrees of improvement: the application of AGVs and task path planning. To handle conflict coordination and AGV cluster path planning, a shortest path planning algorithm based on the A* search algorithm was proposed, and the traffic control law was enhanced. The initial population of genetic algorithms, which used greedy algorithms to solve problems, was found to be too large in terms of task distribution. To address this, the introduction of a few random individuals ensured population diversity and helped avoid local optima. Numerical experiments demonstrated a significantly accelerated convergence rate towards the optimal solution. |
| first_indexed | 2024-03-10T23:23:21Z |
| format | Article |
| id | doaj.art-32f926585aab4295a4df63d2ca28768d |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T23:23:21Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-32f926585aab4295a4df63d2ca28768d2023-11-19T08:06:10ZengMDPI AGEnergies1996-10732023-08-011617631010.3390/en16176310Design of an Intelligent Shop Scheduling System Based on Internet of ThingsMaoyun Zhang0Yuheng Jiang1Chuan Wan2Chen Tang3Boyan Chen4Huizhuang Xi5Faculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaFaculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaSchool of Information and Science and Technology, Northeast Normal University, Changchun 130024, ChinaFaculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaFaculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaFaculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, ChinaIn order to optimize the functionality of automated guidance vehicles (AGVs) in logistics workshops, a wireless charging and task-based logistics intelligent dispatch system was developed based on the Internet of Things. This system aimed to improve freight efficiency in the workshop’s logistics system. The scheduling system successfully addressed the round-trip scheduling issue between AGVs and multiple tasks through two degrees of improvement: the application of AGVs and task path planning. To handle conflict coordination and AGV cluster path planning, a shortest path planning algorithm based on the A* search algorithm was proposed, and the traffic control law was enhanced. The initial population of genetic algorithms, which used greedy algorithms to solve problems, was found to be too large in terms of task distribution. To address this, the introduction of a few random individuals ensured population diversity and helped avoid local optima. Numerical experiments demonstrated a significantly accelerated convergence rate towards the optimal solution.https://www.mdpi.com/1996-1073/16/17/6310AGV clusterInternet of Thingsschedulingalgorithm |
| spellingShingle | Maoyun Zhang Yuheng Jiang Chuan Wan Chen Tang Boyan Chen Huizhuang Xi Design of an Intelligent Shop Scheduling System Based on Internet of Things Energies AGV cluster Internet of Things scheduling algorithm |
| title | Design of an Intelligent Shop Scheduling System Based on Internet of Things |
| title_full | Design of an Intelligent Shop Scheduling System Based on Internet of Things |
| title_fullStr | Design of an Intelligent Shop Scheduling System Based on Internet of Things |
| title_full_unstemmed | Design of an Intelligent Shop Scheduling System Based on Internet of Things |
| title_short | Design of an Intelligent Shop Scheduling System Based on Internet of Things |
| title_sort | design of an intelligent shop scheduling system based on internet of things |
| topic | AGV cluster Internet of Things scheduling algorithm |
| url | https://www.mdpi.com/1996-1073/16/17/6310 |
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