Optimization of A comprehensive dispatching system based on ant colony algorithm and dynamic weight power dispatching strategy

In this study, we explored an optimization method for a comprehensive power dispatching system based on the fusion of ant colony algorithm and dynamic weight scheduling strategy. Firstly, the limitations of the existing scheduling system are introduced. Then, the proposed optimization methods are elaborated in detail, including the basic principle of ant colony algorithm, the design of dynamic weight scheduling strategy, and the fusion mode of the two. A large number of experimental data prove that this method is superior to the traditional scheduling method. Experimental results show that the integrated scheduling system optimization method based on ant colony algorithm and dynamic weight scheduling strategy significantly improves the scheduling efficiency and resource utilization. Specifically, the method reduces the average dispatch time by 20% and improves the resource utilization by 15% when dealing with large-scale power dispatching problems. This indicates that the method has high practical value and can provide strong support for the optimization of scheduling system in related fields.

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Publication Details

Journal
Scientific Reports
Published
2025-11-11
DOI
https://doi.org/10.1038/s41598-025-22913-3
Primary Topic
AI and Multimedia in Education
Type
article
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article

Optimization of A comprehensive dispatching system based on ant colony algorithm and dynamic weight power dispatching strategy

Haikun Teng, Zhiqiang Xie, J. Ming
Scientific Reports
AI and Multimedia in Education
article

Optimization of A comprehensive dispatching system based on ant colony algorithm and dynamic weight power dispatching strategy

Haikun Teng, Zhiqiang Xie, J. Ming
article en

Abstract

In this study, we explored an optimization method for a comprehensive power dispatching system based on the fusion of ant colony algorithm and dynamic weight scheduling strategy. Firstly, the limitations of the existing scheduling system are introduced. Then, the proposed optimization methods are elaborated in detail, including the basic principle of ant colony algorithm, the design of dynamic weight scheduling strategy, and the fusion mode of the two. A large number of experimental data prove that this method is superior to the traditional scheduling method. Experimental results show that the integrated scheduling system optimization method based on ant colony algorithm and dynamic weight scheduling strategy significantly improves the scheduling efficiency and resource utilization. Specifically, the method reduces the average dispatch time by 20% and improves the resource utilization by 15% when dealing with large-scale power dispatching problems. This indicates that the method has high practical value and can provide strong support for the optimization of scheduling system in related fields.

Scientific ReportsVol. 15(1)
Harbin University of Science and Technology (CN), Heilongjiang Vocational College of Art (CN)
Openalex Percentile: Top 82%
AI and Multimedia in Education
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Optimization of A comprehensive dispatching system based on ant colony algorithm and dynamic weight power dispatching strategy — Haikun Teng, Zhiqiang Xie, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS