Research on production scheduling method considering multidimensional testing ability of employees

Renhao Wang

doi:10.1117/12.3051389

18 November 2024 Research on production scheduling method considering multidimensional testing ability of employees

Renhao Wang

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134032Z (2024) https://doi.org/10.1117/12.3051389
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

In complex inspection procedures, there is a significant variation among different personnel. However, the existing personnel scheduling methods often treat individuals as similar or identical entities, which can result in low overall yield and substantial losses for the company. In this context, a study was conducted to improve the yield from the perspective of personnel scheduling in inspections. Based on the interception capabilities of different personnel for various types of defects, and in combination with the concentrations of different defect types for different models, a hybrid algorithm combining genetic algorithms and particle swarm optimization algorithms with elite decision-making was proposed. This algorithm allows for the selection of suitable personnel from the personnel pool, followed by targeted personnel scheduling based on the defect concentrations specific to each personnel and model. This ensures that the appropriate personnel are assigned to the corresponding models, thereby maximizing the yield for all models. Through experiments and result analysis on different scenarios, as well as comparisons with other algorithms, the test results demonstrate the superiority of this method in terms of convergence and optimization capability. This approach offers a new perspective on scheduling based on the multidimensional testing capability of employees, providing valuable insights for optimizing production and scheduling in enterprises.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Renhao Wang "Research on production scheduling method considering multidimensional testing ability of employees", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134032Z (18 November 2024); https://doi.org/10.1117/12.3051389

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KEYWORDS

Particle swarm optimization

Genetic algorithms

Particles

Mathematical optimization

Inspection

Decision making

Matrices

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