A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks
The dynamic-scheduling problem of transmission tasks (DSTT) is an important problem in the daily work of radio and television transmission stations. The transmission effect obtained by the greedy algorithm for task allocation is poor. In the case of more tasks and equipment and smaller time division...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/7/4353 |
| _version_ | 1797608335062597632 |
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| author | Xinzhe Wang Wenbin Yao |
| author_facet | Xinzhe Wang Wenbin Yao |
| author_sort | Xinzhe Wang |
| collection | DOAJ |
| description | The dynamic-scheduling problem of transmission tasks (DSTT) is an important problem in the daily work of radio and television transmission stations. The transmission effect obtained by the greedy algorithm for task allocation is poor. In the case of more tasks and equipment and smaller time division, the precise algorithm cannot complete the calculation within an effective timeframe. In order to solve this problem, this paper proposes a discrete particle swarm optimization algorithm (DPSO), builds a DSTT mathematical model suitable for the DPSO, solves the problem that particle swarm operations are not easy to describe in discrete problems, and redefines the particle motion strategy and adds random disturbance operation in its probabilistic selection model to ensure the effectiveness of the algorithm. In the comparison experiment, the DPSO achieved much higher success rates than the greedy algorithm (GR) and the improved genetic algorithm (IGA). Finally, in the simulation experiment, the result data show that the accuracy of the DPSO outperforms that of the GR and IGA by up to 3.012295% and 0.11115%, respectively, and the efficiency of the DPSO outperforms that of the IGA by up to 69.246%. |
| first_indexed | 2024-03-11T05:43:02Z |
| format | Article |
| id | doaj.art-86f533730f6749f99e9fa36f89a1ed2d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T05:43:02Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-86f533730f6749f99e9fa36f89a1ed2d2023-11-17T16:19:08ZengMDPI AGApplied Sciences2076-34172023-03-01137435310.3390/app13074353A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission TasksXinzhe Wang0Wenbin Yao1College of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaCollege of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe dynamic-scheduling problem of transmission tasks (DSTT) is an important problem in the daily work of radio and television transmission stations. The transmission effect obtained by the greedy algorithm for task allocation is poor. In the case of more tasks and equipment and smaller time division, the precise algorithm cannot complete the calculation within an effective timeframe. In order to solve this problem, this paper proposes a discrete particle swarm optimization algorithm (DPSO), builds a DSTT mathematical model suitable for the DPSO, solves the problem that particle swarm operations are not easy to describe in discrete problems, and redefines the particle motion strategy and adds random disturbance operation in its probabilistic selection model to ensure the effectiveness of the algorithm. In the comparison experiment, the DPSO achieved much higher success rates than the greedy algorithm (GR) and the improved genetic algorithm (IGA). Finally, in the simulation experiment, the result data show that the accuracy of the DPSO outperforms that of the GR and IGA by up to 3.012295% and 0.11115%, respectively, and the efficiency of the DPSO outperforms that of the IGA by up to 69.246%.https://www.mdpi.com/2076-3417/13/7/4353task dynamic schedulingdiscrete particle swarm optimization algorithmprobability selection modelrandom disturbancescheduleevaluation of transmission effect |
| spellingShingle | Xinzhe Wang Wenbin Yao A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks Applied Sciences task dynamic scheduling discrete particle swarm optimization algorithm probability selection model random disturbance schedule evaluation of transmission effect |
| title | A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks |
| title_full | A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks |
| title_fullStr | A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks |
| title_full_unstemmed | A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks |
| title_short | A Discrete Particle Swarm Optimization Algorithm for Dynamic Scheduling of Transmission Tasks |
| title_sort | discrete particle swarm optimization algorithm for dynamic scheduling of transmission tasks |
| topic | task dynamic scheduling discrete particle swarm optimization algorithm probability selection model random disturbance schedule evaluation of transmission effect |
| url | https://www.mdpi.com/2076-3417/13/7/4353 |
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