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| Year | Author | Method | Advantage |
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| 2021 | Wang et al. [4] | Multipopulation collaborative genetic algorithm based on collaborative optimization algorithm for solving FJSP problems | The algorithm has good recommendation performance |
| Szarek [9] and Zheng et al. [11] | A new hybrid convolutional neural network model | The predictive performance of this model is superior to traditional models |
| Chea and Nam [10] | Optimal residual depth neural network image processing technology | This method has high peak and average accuracy |
| Bhola et al. [12] | Introducing optimal genetic algorithm in the optimization research of wireless sensor networks | Finding the optimal path through its fitness function |
| Sahu [14] | Feature selection technology based on genetic algorithm | This technology improves classification accuracy |
| Gong et al. [15] | A new nondominated synthetic adaptive sorting algorithm | Optimizable multiobjective flexible job shop scheduling |
| Tan et al. [16] | A flexible job-shop scheduling scheme with dual resource constraints | This method enhances local search functionality and achieves better scheduling |
| Wang et al. [17] | A hybrid algorithm based on grey wolf and invasive weeds | This algorithm can effectively solve the flexible job-shop scheduling problem |
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| 2022 | Shafiq et al. [6], Shahzad [7], and Fard [8] | Prediction method based on artificial neural network | This method has high prediction accuracy |
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