| Issue |
ITM Web Conf.
Volume 77, 2025
2025 International Conference on Education, Management and Information Technology (EMIT 2025)
|
|
|---|---|---|
| Article Number | 01022 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/itmconf/20257701022 | |
| Published online | 02 July 2025 | |
Research on PBS buffer scheduling strategy problems based on genetic algorithms
School of Artificial Intelligence and Software, Liaoning Petrochemical University Fushun 130001, China
* Corresponding author: zhangyaodan0519@163.com
In automotive manufacturing, production constraints between the painting and assembly workshops often disrupt the vehicle production sequence. To solve this, a Painted Body Store (PBS) buffer was introduced. This adjusts the sequence from painting to match the assembly workshop's needs.A model was created using rules to match vehicle and channel attributes, forming an initial exit sequence for painted vehicles. A genetic algorithm optimized vehicle selection from the PBS, adhering to constraints.Analysis showed this method improved efficiency by nearly 40% compared to traditional linear scheduling. This highlights its effectiveness in optimizing automotive manufacturing.
© The Authors, published by EDP Sciences, 2025
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