基于改进SA算法在智能制造生产调动模型研究

智能制造生产调动是一个复杂的多目标优化问题,传统的生产调动方法多采用启发式方法,在面对复杂的制造环境,传统方法可能会出现早熟收敛或搜索精度下降的问题;因此为了解决这些问题,研究构建了基于改进SA算法的智能制造生产调动模型;首先对SA算法进行了优化,其次利用优化后的算法构建了生产调动模型,最后通过仿真实验去验证模式算法的性能。实验结果表明,在数据集中,真实值、模型方法和传统方法的平均完成时间分别为85.33min、89.92min和93.81min,其中模型方法与真实值的差距仅为4.59min。这说明模型方法可以用于解决现有生产模式存在拖期的情况,及时完成生产任务。模型算法能够为智能制造生产调动提供新的思路。

Application of Improved SA Algorithm for Scheduling Optimization of Industrial Automation Tasks in Intelligent Manufacturing

Smart manufacturing production mobilization is a complex multi-objective optimization problem. Traditional production mobilization methods mostly use heuristics, and in the face of complex manufacturing environments, traditional methods may have problems of premature convergence or reduced search accuracy; therefore, in order to solve these problems, the study constructs a smart manufacturing production mobilization model based on the improved SA algorithm; firstly, the SA algorithm is optimized, and secondly, the optimized algorithm is used to construct a production mobilization model. The SA algorithm is optimized, the optimized algorithm is used to construct the production mobilization model, and finally the performance of the model algorithm is verified through simulation experiments. The experimental results show that the average completion time of real value, model method and traditional method are 85.33 min, 89.92 min and 93.81 min respectively in the dataset, and the difference between model method and real value is only 4.59 min. This indicates that the model method can be used to solve the situation of delay in the existing production model and complete the production tasks in time. The model algorithm can provide new ideas for smart manufacturing production mobilization.